Klosa, Elizabeth; Hisey, Rebecca; Hashtrudi-Zaad, Kian; Zevin, Boris; Ungi, Tamas; Fichtinger, Gabor
Comparing methods of identifying tissues for workflow recognition of simulated open hernia repair Conference
2023.
@conference{nokey,
title = {Comparing methods of identifying tissues for workflow recognition of simulated open hernia repair},
author = {Elizabeth Klosa and Rebecca Hisey and Kian Hashtrudi-Zaad and Boris Zevin and Tamas Ungi and Gabor Fichtinger},
url = {https://imno.ca/sites/default/files/ImNO2023Proceedings.pdf},
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Rebecca Hisey Elizabeth Klosa, Kian Hashtrudi-Zaad
Comparing methods of identifying tissues for workflow recognition of simulated open hernia repair Conference
2023.
@conference{nokey,
title = {Comparing methods of identifying tissues for workflow recognition of simulated open hernia repair},
author = {Elizabeth Klosa, Rebecca Hisey, Kian Hashtrudi-Zaad, Boris Zevin, Tamas Ungi, Gabor Fichtinger},
year = {2023},
date = {2023-03-24},
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Austin, Catherine; Hisey, Rebecca; O'Driscoll, Olivia; Ungi, Tamas; Fichtinger, Gabor
Using uncertainty quantification to improve reliability of video-based skill assessment metrics in central venous catheterization Journal Article
In: vol. 12466, pp. 84-88, 2023.
@article{fichtinger2023y,
title = {Using uncertainty quantification to improve reliability of video-based skill assessment metrics in central venous catheterization},
author = {Catherine Austin and Rebecca Hisey and Olivia O'Driscoll and Tamas Ungi and Gabor Fichtinger},
url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12466/124660C/Using-uncertainty-quantification-to-improve-reliability-of-video-based-skill/10.1117/12.2654419.short},
year = {2023},
date = {2023-01-01},
volume = {12466},
pages = {84-88},
publisher = {SPIE},
abstract = {Computed-based skill assessment relies on accurate metrics to provide comprehensive feedback to trainees. Improving the accuracy of video-based metrics computed using object detection is generally done by improving the performance of the object detection network, however increasing its performance requires resources that cannot always be obtained. This study aims to improve the accuracy of metrics in central venous catheterization without requiring a high performing object detection network by removing false positive predictions identified using uncertainty quantification. The uncertainty for each bounding box was calculated using an entropy equation. The uncertainties were then compared to an uncertainty threshold computed using the optimal point of a Receiver Operating Characteristic curve. Predictions were removed if the uncertainty fell below the predefined threshold. 50 videos were recorded and …},
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Computed-based skill assessment relies on accurate metrics to provide comprehensive feedback to trainees. Improving the accuracy of video-based metrics computed using object detection is generally done by improving the performance of the object detection network, however increasing its performance requires resources that cannot always be obtained. This study aims to improve the accuracy of metrics in central venous catheterization without requiring a high performing object detection network by removing false positive predictions identified using uncertainty quantification. The uncertainty for each bounding box was calculated using an entropy equation. The uncertainties were then compared to an uncertainty threshold computed using the optimal point of a Receiver Operating Characteristic curve. Predictions were removed if the uncertainty fell below the predefined threshold. 50 videos were recorded and …
Morton, David; Connolly, Laura; Groves, Leah; Sunderland, Kyle; Jamzad, Amoon; Rudan, John F; Fichtinger, Gabor; Ungi, Tamas; Mousavi, Parvin
Tracked tissue sensing for tumor bed inspection Journal Article
In: vol. 12466, pp. 378-385, 2023.
@article{fichtinger2023x,
title = {Tracked tissue sensing for tumor bed inspection},
author = {David Morton and Laura Connolly and Leah Groves and Kyle Sunderland and Amoon Jamzad and John F Rudan and Gabor Fichtinger and Tamas Ungi and Parvin Mousavi},
url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12466/124661K/Tracked-tissue-sensing-for-tumor-bed-inspection/10.1117/12.2654217.short},
year = {2023},
date = {2023-01-01},
volume = {12466},
pages = {378-385},
publisher = {SPIE},
abstract = {Up to 30% of breast-conserving surgery patients require secondary surgery to remove cancerous tissue missed in the initial intervention. We hypothesize that tracked tissue sensing can improve the success rate of breast-conserving surgery. Tissue sensor tracking allows the surgeon to intraoperatively scan the tumor bed for leftover cancerous tissue. In this study, we characterize the performance of our tracked optical scanning testbed using an experimental pipeline. We assess the Dice similarity coefficient, accuracy, and latency of the testbed.},
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Up to 30% of breast-conserving surgery patients require secondary surgery to remove cancerous tissue missed in the initial intervention. We hypothesize that tracked tissue sensing can improve the success rate of breast-conserving surgery. Tissue sensor tracking allows the surgeon to intraoperatively scan the tumor bed for leftover cancerous tissue. In this study, we characterize the performance of our tracked optical scanning testbed using an experimental pipeline. We assess the Dice similarity coefficient, accuracy, and latency of the testbed.
Barr, Keiran; Hookey, Lawrence; Ungi, Tamas; Fichtinger, Gabor; Holden, Matthew
Analyzing colonoscopy training learning curves using comparative hand tracking assessment Journal Article
In: vol. 12466, pp. 466-472, 2023.
@article{fichtinger2023w,
title = {Analyzing colonoscopy training learning curves using comparative hand tracking assessment},
author = {Keiran Barr and Lawrence Hookey and Tamas Ungi and Gabor Fichtinger and Matthew Holden},
url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12466/124661Y/Analyzing-colonoscopy-training-learning-curves-using-comparative-hand-tracking-assessment/10.1117/12.2654309.short},
year = {2023},
date = {2023-01-01},
volume = {12466},
pages = {466-472},
publisher = {SPIE},
abstract = {A competency-based approach for colonoscopy training is particularly important, since the amount of practice required for proficiency varies widely between trainees. Though numerous objective proficiency assessment frameworks have been validated in the literature, these frameworks rely on expert observers. This process is time-consuming, and as a result, there has been increased interest in automated proficiency rating of colonoscopies. This work aims to investigate sixteen automatically computed performance metrics, and whether they can measure improvements in novices following a series of practice attempts. This involves calculating motion-tracking parameters for three groups: untrained novices, those same novices after undergoing training exercises, and experts. Both groups had electromagnetic tracking markers fixed to their hands and the scope tip. Each participant performed eight testing …},
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A competency-based approach for colonoscopy training is particularly important, since the amount of practice required for proficiency varies widely between trainees. Though numerous objective proficiency assessment frameworks have been validated in the literature, these frameworks rely on expert observers. This process is time-consuming, and as a result, there has been increased interest in automated proficiency rating of colonoscopies. This work aims to investigate sixteen automatically computed performance metrics, and whether they can measure improvements in novices following a series of practice attempts. This involves calculating motion-tracking parameters for three groups: untrained novices, those same novices after undergoing training exercises, and experts. Both groups had electromagnetic tracking markers fixed to their hands and the scope tip. Each participant performed eight testing …
Ehrlich, J; Yeung, C; Kaufman, M; Jamzad, A; Rudan, J; Mousavi, P; Fichtinger, G; Ungi, T
Determining the time-delay of a mass spectrometry-based tissue sensor Journal Article
In: vol. 12466, pp. 324-327, 2023.
@article{fichtinger2023v,
title = {Determining the time-delay of a mass spectrometry-based tissue sensor},
author = {J Ehrlich and C Yeung and M Kaufman and A Jamzad and J Rudan and P Mousavi and G Fichtinger and T Ungi},
url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12466/124661D/Determining-the-time-delay-of-a-mass-spectrometry-based-tissue/10.1117/12.2654359.short},
year = {2023},
date = {2023-01-01},
volume = {12466},
pages = {324-327},
publisher = {SPIE},
abstract = {Breast cancer commonly requires surgical treatment. A procedure used to remove breast cancer is lumpectomy, which removes a minimal healthy tissue margin surrounding the tumor, called a negative margin. A cancer-free margin is difficult to achieve because tumors are not visible or palpable, and the breast deforms during surgery. One notable solution is Rapid Evaporative Ionization Mass Spectrometry (REIMS), which differentiates tumor from healthy tissue with high accuracy from the vapor generated by the surgical cautery. REIMS combined with navigation could detect where the surgical cautery breaches tumor tissue. However, fusing position tracking and REIMS data for navigation is challenging. REIMS has a time-delay dependent on a series of factors. Our objective was to evaluate REIMS time-delay for surgical navigation. The average time-delay of REIMS classifications was measured by video …},
keywords = {},
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Breast cancer commonly requires surgical treatment. A procedure used to remove breast cancer is lumpectomy, which removes a minimal healthy tissue margin surrounding the tumor, called a negative margin. A cancer-free margin is difficult to achieve because tumors are not visible or palpable, and the breast deforms during surgery. One notable solution is Rapid Evaporative Ionization Mass Spectrometry (REIMS), which differentiates tumor from healthy tissue with high accuracy from the vapor generated by the surgical cautery. REIMS combined with navigation could detect where the surgical cautery breaches tumor tissue. However, fusing position tracking and REIMS data for navigation is challenging. REIMS has a time-delay dependent on a series of factors. Our objective was to evaluate REIMS time-delay for surgical navigation. The average time-delay of REIMS classifications was measured by video …
Elmi, H; Jamzad, A; Sharp, M; Rodgers, JR; Kaufmann, M; Jamaspishvili, T; Iseman, R; Berman, D; Rudan, J; Fichtinger, G; Mousavi, P
ViPRE: an open-source software implementation for end-to-end analysis of mass spectrometry data Journal Article
In: vol. 12466, pp. 487-494, 2023.
@article{fichtinger2023u,
title = {ViPRE: an open-source software implementation for end-to-end analysis of mass spectrometry data},
author = {H Elmi and A Jamzad and M Sharp and JR Rodgers and M Kaufmann and T Jamaspishvili and R Iseman and D Berman and J Rudan and G Fichtinger and P Mousavi},
url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12466/1246621/ViPRE–an-open-source-software-implementation-for-end-to/10.1117/12.2654425.short},
year = {2023},
date = {2023-01-01},
volume = {12466},
pages = {487-494},
publisher = {SPIE},
abstract = {Mass Spectrometry Imaging (MSI) is a powerful tool capable of visualizing molecular patterns to identify disease markers in tissue analysis. However, data analysis is computationally heavy and currently time-consuming as there is no single platform capable of performing the entire preprocessing, visualization, and analysis pipeline end-to-end. Using different software tools and file formats required for such tools also makes the process prone to error. The purpose of this work is to develop a free, open-source software implementation called “Visualization, Preprocessing, and Registration Environment” (ViPRE), capable of end-to-end analysis of MSI data. ViPRE was developed to provide various functionalities required for MSI analysis including data import, data visualization, data registration, Region of Interest (ROI) selection, spectral data alignment and data analysis. The software implementation is offered as an …},
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}
Mass Spectrometry Imaging (MSI) is a powerful tool capable of visualizing molecular patterns to identify disease markers in tissue analysis. However, data analysis is computationally heavy and currently time-consuming as there is no single platform capable of performing the entire preprocessing, visualization, and analysis pipeline end-to-end. Using different software tools and file formats required for such tools also makes the process prone to error. The purpose of this work is to develop a free, open-source software implementation called “Visualization, Preprocessing, and Registration Environment” (ViPRE), capable of end-to-end analysis of MSI data. ViPRE was developed to provide various functionalities required for MSI analysis including data import, data visualization, data registration, Region of Interest (ROI) selection, spectral data alignment and data analysis. The software implementation is offered as an …
Radcliffe, Olivia; Connolly, Laura; Ungi, Tamas; Yeo, Caitlin; Rudan, John F; Fichtinger, Gabor; Mousavi, Parvin
Navigated surgical resection cavity inspection for breast conserving surgery Journal Article
In: vol. 12466, pp. 234-241, 2023.
@article{fichtinger2023t,
title = {Navigated surgical resection cavity inspection for breast conserving surgery},
author = {Olivia Radcliffe and Laura Connolly and Tamas Ungi and Caitlin Yeo and John F Rudan and Gabor Fichtinger and Parvin Mousavi},
url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12466/124660Z/Navigated-surgical-resection-cavity-inspection-for-breast-conserving-surgery/10.1117/12.2654015.short},
year = {2023},
date = {2023-01-01},
volume = {12466},
pages = {234-241},
publisher = {SPIE},
abstract = {Up to 40% of Breast Conserving Surgery (BCS) patients must undergo repeat surgery because cancer is left behind in the resection cavity. The mobility of the breast resection cavity makes it difficult to localize residual cancer and, therefore, cavity shaving is a common technique for cancer removal. Cavity shaving involves removing an additional layer of tissue from the entire resection cavity, often resulting in unnecessary healthy tissue loss. In this study, we demonstrated a navigation system and open-source software module that facilitates visualization of the breast resection cavity for targeted localization of residual cancer.},
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Up to 40% of Breast Conserving Surgery (BCS) patients must undergo repeat surgery because cancer is left behind in the resection cavity. The mobility of the breast resection cavity makes it difficult to localize residual cancer and, therefore, cavity shaving is a common technique for cancer removal. Cavity shaving involves removing an additional layer of tissue from the entire resection cavity, often resulting in unnecessary healthy tissue loss. In this study, we demonstrated a navigation system and open-source software module that facilitates visualization of the breast resection cavity for targeted localization of residual cancer.
Klosa, Elizabeth; Hisey, Rebecca; Hashtrudi-Zaad, Kian; Zevin, Boris; Ungi, Tamas; Fichtinger, Gabor
Identifying tool-tissue interactions to distinguish steps in simulated open inguinal hernia repair Journal Article
In: vol. 12466, pp. 479-486, 2023.
@article{fichtinger2023s,
title = {Identifying tool-tissue interactions to distinguish steps in simulated open inguinal hernia repair},
author = {Elizabeth Klosa and Rebecca Hisey and Kian Hashtrudi-Zaad and Boris Zevin and Tamas Ungi and Gabor Fichtinger},
url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12466/1246620/Identifying-tool-tissue-interactions-to-distinguish-steps-in-simulated-open/10.1117/12.2654394.short},
year = {2023},
date = {2023-01-01},
volume = {12466},
pages = {479-486},
publisher = {SPIE},
abstract = {As medical education adopts a competency-based training approach, assessment of skills and timely provision of formative feedback is required. Provision of such assessment and feedback places a substantial time burden on surgeons. To reduce this time burden, we look to develop a computer-assisted training platform to provide both instruction and feedback to residents learning open Inguinal Hernia Repairs (IHR). To provide feedback on residents’ technical skills, we must first find a method of workflow recognition of the IHR. We thus aim to recognize and distinguish between workflow steps of an open IHR based on the presence and frequencies of different tool-tissue interactions occurring during each step. Based on ground truth tissue segmentations and tool bounding boxes, we identify the visible tissues within a bounding box. This provides an estimation of which tissues a tool is interacting with. The …},
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}
As medical education adopts a competency-based training approach, assessment of skills and timely provision of formative feedback is required. Provision of such assessment and feedback places a substantial time burden on surgeons. To reduce this time burden, we look to develop a computer-assisted training platform to provide both instruction and feedback to residents learning open Inguinal Hernia Repairs (IHR). To provide feedback on residents’ technical skills, we must first find a method of workflow recognition of the IHR. We thus aim to recognize and distinguish between workflow steps of an open IHR based on the presence and frequencies of different tool-tissue interactions occurring during each step. Based on ground truth tissue segmentations and tool bounding boxes, we identify the visible tissues within a bounding box. This provides an estimation of which tissues a tool is interacting with. The …
Syeda, Ayesha; Fooladgar, Fahimeh; Jamzad, Amoon; Srikanthan, Dilakshan; Kaufmann, Martin; Ren, Kevin; Engel, Jay; Walker, Ross; Merchant, Shaila; McKay, Doug; Varma, Sonal; Fichtinger, Gabor; Rudan, John; Mousavi, Parvin
Self-supervised learning and uncertainty estimation for surgical margin detection Journal Article
In: vol. 12466, pp. 76-83, 2023.
@article{fichtinger2023r,
title = {Self-supervised learning and uncertainty estimation for surgical margin detection},
author = {Ayesha Syeda and Fahimeh Fooladgar and Amoon Jamzad and Dilakshan Srikanthan and Martin Kaufmann and Kevin Ren and Jay Engel and Ross Walker and Shaila Merchant and Doug McKay and Sonal Varma and Gabor Fichtinger and John Rudan and Parvin Mousavi},
url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12466/124660B/Self-supervised-learning-and-uncertainty-estimation-for-surgical-margin-detection/10.1117/12.2654104.short},
year = {2023},
date = {2023-01-01},
volume = {12466},
pages = {76-83},
publisher = {SPIE},
abstract = {Up to 35% of breast-conserving surgeries fail to resect all the tumors completely. Ideally, machine learning methods using the iKnife data, which uses Rapid Evaporative Ionization Mass Spectrometry (REIMS), can be utilized to predict tissue type in real-time during surgery, resulting in better tumor resections. As REIMS data is heterogeneous and weakly labeled, and datasets are often small, model performance and reliability can be adversely affected. Self-supervised training and uncertainty estimation of the prediction can be used to mitigate these challenges by learning the signatures of input data without their label as well as including predictive confidence in output reporting. We first design an autoencoder model using a reconstruction pretext task as a self-supervised pretraining step without considering tissue type. Next, we construct our uncertainty-aware classifier using the encoder part of the model with …},
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Up to 35% of breast-conserving surgeries fail to resect all the tumors completely. Ideally, machine learning methods using the iKnife data, which uses Rapid Evaporative Ionization Mass Spectrometry (REIMS), can be utilized to predict tissue type in real-time during surgery, resulting in better tumor resections. As REIMS data is heterogeneous and weakly labeled, and datasets are often small, model performance and reliability can be adversely affected. Self-supervised training and uncertainty estimation of the prediction can be used to mitigate these challenges by learning the signatures of input data without their label as well as including predictive confidence in output reporting. We first design an autoencoder model using a reconstruction pretext task as a self-supervised pretraining step without considering tissue type. Next, we construct our uncertainty-aware classifier using the encoder part of the model with …
Yeung, Chris; Ehrlich, Joshua; Jamzad, Amoon; Kaufmann, Martin; Rudan, John; Engel, Cecil Jay; Mousavi, Parvin; Ungi, Tamas; Fichtinger, Gabor
Cautery trajectory analysis for evaluation of resection margins in breast-conserving surgery Journal Article
In: vol. 12466, pp. 495-501, 2023.
@article{fichtinger2023q,
title = {Cautery trajectory analysis for evaluation of resection margins in breast-conserving surgery},
author = {Chris Yeung and Joshua Ehrlich and Amoon Jamzad and Martin Kaufmann and John Rudan and Cecil Jay Engel and Parvin Mousavi and Tamas Ungi and Gabor Fichtinger},
url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12466/1246622/Cautery-trajectory-analysis-for-evaluation-of-resection-margins-in-breast/10.1117/12.2654497.short},
year = {2023},
date = {2023-01-01},
volume = {12466},
pages = {495-501},
publisher = {SPIE},
abstract = {After breast-conserving surgery, positive margins occur when breast cancer cells are found on the resection margin, leading to a higher chance of recurrence and the need for repeat surgery. The NaviKnife is an electromagnetic tracking-based surgical navigation system that helps to provide visual and spatial feedback to the surgeon. In this study, we conduct a gross evaluation of this navigation system with respect to resection margins. The trajectory of the surgical cautery relative to ultrasound-visible tumor will be visualized, and its distance and location from the tumor will be compared with pathology reports. Six breast-conserving surgery cases that resulted in positive margins were performed using the NaviKnife system. Trackers were placed on the surgical tools and their positions in three-dimensional space were recorded throughout the procedure. The closest distance between the cautery and the tumor …},
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}
After breast-conserving surgery, positive margins occur when breast cancer cells are found on the resection margin, leading to a higher chance of recurrence and the need for repeat surgery. The NaviKnife is an electromagnetic tracking-based surgical navigation system that helps to provide visual and spatial feedback to the surgeon. In this study, we conduct a gross evaluation of this navigation system with respect to resection margins. The trajectory of the surgical cautery relative to ultrasound-visible tumor will be visualized, and its distance and location from the tumor will be compared with pathology reports. Six breast-conserving surgery cases that resulted in positive margins were performed using the NaviKnife system. Trackers were placed on the surgical tools and their positions in three-dimensional space were recorded throughout the procedure. The closest distance between the cautery and the tumor …
Hashtrudi-Zaad, Kian; Hisey, Rebecca; Klosa, Elizabeth; Zevin, Boris; Ungi, Tamas; Fichtinger, Gabor
Using object detection for surgical tool recognition in simulated open inguinal hernia repair surgery Journal Article
In: vol. 12466, pp. 96-101, 2023.
@article{fichtinger2023p,
title = {Using object detection for surgical tool recognition in simulated open inguinal hernia repair surgery},
author = {Kian Hashtrudi-Zaad and Rebecca Hisey and Elizabeth Klosa and Boris Zevin and Tamas Ungi and Gabor Fichtinger},
url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12466/124660E/Using-object-detection-for-surgical-tool-recognition-in-simulated-open/10.1117/12.2654393.short},
year = {2023},
date = {2023-01-01},
volume = {12466},
pages = {96-101},
publisher = {SPIE},
abstract = {Following the shift from time-based medical education to a competency-based approach, a computer-assisted training platform would help relieve some of the new time burden placed on physicians. A vital component of these platforms is the computation of competency metrics which are based on surgical tool motion. Recognizing the class and motion of surgical tools is one step in the development of a training platform. Object detection can achieve tool recognition. While previous literature has reported on tool recognition in minimally invasive surgeries, open surgeries have not received the same attention. Open Inguinal Hernia Repair (OIHR), a common surgery that general surgery residents must learn, is an example of such surgeries. We present a method for object detection to recognize surgical tools in simulated OIHR. Images were extracted from six video recordings of OIHR performed on phantoms. Tools …},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Following the shift from time-based medical education to a competency-based approach, a computer-assisted training platform would help relieve some of the new time burden placed on physicians. A vital component of these platforms is the computation of competency metrics which are based on surgical tool motion. Recognizing the class and motion of surgical tools is one step in the development of a training platform. Object detection can achieve tool recognition. While previous literature has reported on tool recognition in minimally invasive surgeries, open surgeries have not received the same attention. Open Inguinal Hernia Repair (OIHR), a common surgery that general surgery residents must learn, is an example of such surgeries. We present a method for object detection to recognize surgical tools in simulated OIHR. Images were extracted from six video recordings of OIHR performed on phantoms. Tools …
March, Lucas; Rodgers, Jessica R.; Hisey, Rebecca; Jamzad, Amoon; Santilli, AML; McKay, D; Rudan, JF; Kaufmann, M; Ren, KYM; Fichtinger, G; Mousavi, P
Cautery tool state detection using deep learning on intraoperative surgery videos Journal Article
In: vol. 12466, pp. 89-95, 2023.
@article{fichtinger2023o,
title = {Cautery tool state detection using deep learning on intraoperative surgery videos},
author = {Lucas March and Jessica R. Rodgers and Rebecca Hisey and Amoon Jamzad and AML Santilli and D McKay and JF Rudan and M Kaufmann and KYM Ren and G Fichtinger and P Mousavi},
url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12466/124660D/Cautery-tool-state-detection-using-deep-learning-on-intraoperative-surgery/10.1117/12.2654234.short},
year = {2023},
date = {2023-01-01},
urldate = {2023-01-01},
volume = {12466},
pages = {89-95},
publisher = {SPIE},
abstract = {Treatment for Basal Cell Carcinoma (BCC) includes an excisional surgery to remove cancerous tissues, using a cautery tool to make burns along a defined resection margin around the tumor. Margin evaluation occurs post-surgically, requiring repeat surgery if positive margins are detected. Rapid Evaporative Ionization Mass Spectrometry (REIMS) can help distinguish healthy and cancerous tissue but does not provide spatial information about the cautery tool location where the spectra are acquired. We propose using intraoperative surgical video recordings and deep learning to provide surgeons with guidance to locate sites of potential positive margins. Frames from 14 intraoperative videos of BCC surgery were extracted and used to train a sequence of networks. The first network extracts frames showing surgery in-progress, then, an object detection network localizes the cautery tool and resection margin. Finally …},
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}
Treatment for Basal Cell Carcinoma (BCC) includes an excisional surgery to remove cancerous tissues, using a cautery tool to make burns along a defined resection margin around the tumor. Margin evaluation occurs post-surgically, requiring repeat surgery if positive margins are detected. Rapid Evaporative Ionization Mass Spectrometry (REIMS) can help distinguish healthy and cancerous tissue but does not provide spatial information about the cautery tool location where the spectra are acquired. We propose using intraoperative surgical video recordings and deep learning to provide surgeons with guidance to locate sites of potential positive margins. Frames from 14 intraoperative videos of BCC surgery were extracted and used to train a sequence of networks. The first network extracts frames showing surgery in-progress, then, an object detection network localizes the cautery tool and resection margin. Finally …
Alqaoud, Motaz; Plemmons, John; Feliberti, Eric; Kaipa, Krishnanand; Fichtinger, Gabor; Xiao, Yiming; Rashid, Tanweer; Audette, Michel
Multi-Material, Approach-Guided, Controlled-Resolution Breast Meshing for Fe-Based Interactive Surgery Simulation Journal Article
In: pp. 402-412, 2023.
@article{fichtinger2023n,
title = {Multi-Material, Approach-Guided, Controlled-Resolution Breast Meshing for Fe-Based Interactive Surgery Simulation},
author = {Motaz Alqaoud and John Plemmons and Eric Feliberti and Krishnanand Kaipa and Gabor Fichtinger and Yiming Xiao and Tanweer Rashid and Michel Audette},
url = {https://ieeexplore.ieee.org/abstract/document/10155366/},
year = {2023},
date = {2023-01-01},
pages = {402-412},
publisher = {IEEE},
abstract = {This paper proposes a guided, controlled resolution framework for 3D multi-material meshing. Using data from magnetic resonance (MR) images, we efficiently focused on demonstrating our framework for patient-specific breast cases. As a result, we can preserve the shared boundaries and enhance the resolution without negating the aspect of simulation computing time needed for finite element analysis (FEA). Our output is a high-quality volumetric mesh comprising 21K cells representing the three main parts for breast surgery simulation and planning, fat, fibroglandular (FGT), and tumor mass. Our approach combines three steps, surface meshing, surface mesh decimation, and generating a volumetric mesh. We showed experimental results for every stage and compared our final output to other literature, proving our method's efficiency in an accurate, simple, and high-quality presentation of a patient-specific …},
keywords = {},
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tppubtype = {article}
}
This paper proposes a guided, controlled resolution framework for 3D multi-material meshing. Using data from magnetic resonance (MR) images, we efficiently focused on demonstrating our framework for patient-specific breast cases. As a result, we can preserve the shared boundaries and enhance the resolution without negating the aspect of simulation computing time needed for finite element analysis (FEA). Our output is a high-quality volumetric mesh comprising 21K cells representing the three main parts for breast surgery simulation and planning, fat, fibroglandular (FGT), and tumor mass. Our approach combines three steps, surface meshing, surface mesh decimation, and generating a volumetric mesh. We showed experimental results for every stage and compared our final output to other literature, proving our method's efficiency in an accurate, simple, and high-quality presentation of a patient-specific …
Groves, Leah A; Keita, Mohamed; Talla, Saidou; Kikinis, Ron; Fichtinger, Gabor; Mousavi, Parvin; Camara, Mamadou
A Review of Low-cost Ultrasound Compatible Phantoms Journal Article
In: 2023.
@article{fichtinger2023m,
title = {A Review of Low-cost Ultrasound Compatible Phantoms},
author = {Leah A Groves and Mohamed Keita and Saidou Talla and Ron Kikinis and Gabor Fichtinger and Parvin Mousavi and Mamadou Camara},
url = {https://ieeexplore.ieee.org/abstract/document/10157973/},
year = {2023},
date = {2023-01-01},
publisher = {IEEE},
abstract = {Ultrasound-compatible phantoms are used to develop novel US-based systems and train simulated medical interventions. The price difference between lab-made and commercially available ultrasound-compatible phantoms lead to the publication of many papers categorized as low-cost in the literature. The aim of this review was to improve the phantom selection process by summarizing the pertinent literature. We compiled papers on US-compatible spine, prostate, vascular, breast, kidney, and li ver phantoms. We reviewed papers for cost and accessibility, providing an overview of the materials, construction time, shelf life, needle insertion limits, and manufacturing and evaluation methods. This information was summarized by anatomy. The clinical application associated with each phantom was also reported for those interested in a particular intervention. Techniques and common practices for building low-cost …},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Ultrasound-compatible phantoms are used to develop novel US-based systems and train simulated medical interventions. The price difference between lab-made and commercially available ultrasound-compatible phantoms lead to the publication of many papers categorized as low-cost in the literature. The aim of this review was to improve the phantom selection process by summarizing the pertinent literature. We compiled papers on US-compatible spine, prostate, vascular, breast, kidney, and li ver phantoms. We reviewed papers for cost and accessibility, providing an overview of the materials, construction time, shelf life, needle insertion limits, and manufacturing and evaluation methods. This information was summarized by anatomy. The clinical application associated with each phantom was also reported for those interested in a particular intervention. Techniques and common practices for building low-cost …
Ndiaye, Fatou Bintou; Groves, Leah; Hisey, Rebecca; Ungi, Tamas; Diop, Idy; Mousavi, Parvin; Fichtinger, Gabor; Camara, Mamadou Samba
Desing and realization of a computer-assisted nephrostomy guidance system Journal Article
In: pp. 1-6, 2023.
@article{fichtinger2023l,
title = {Desing and realization of a computer-assisted nephrostomy guidance system},
author = {Fatou Bintou Ndiaye and Leah Groves and Rebecca Hisey and Tamas Ungi and Idy Diop and Parvin Mousavi and Gabor Fichtinger and Mamadou Samba Camara},
url = {https://ieeexplore.ieee.org/abstract/document/10253146/},
year = {2023},
date = {2023-01-01},
pages = {1-6},
publisher = {IEEE},
abstract = {Background and purpose
Nowadays, computerized nephrostomy techniques exist. Although relatively safe, several factors make it difficult for inexperienced users. A computer-assisted nephrostomy guidance system has been studied to increase the success rate of this intervention and reduce the work and difficulties encountered by the actors.
Methods
To design the system, two methods will be studied. Following this study, this system was designed based on method 2. SmartSysNephro is composed of a hardware part whose manipulations made by the user are visualized and assisted by the computer. This nephrostomy procedure that the user simulates is monitored by webcam. Using the data from this Intel Real Sense webcam, allowed to propose a CNN YOLO model.
Results
The results obtained show that the objectives set have been achieved globally. The SmartSysNephro system gives real time warning …},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Background and purpose
Nowadays, computerized nephrostomy techniques exist. Although relatively safe, several factors make it difficult for inexperienced users. A computer-assisted nephrostomy guidance system has been studied to increase the success rate of this intervention and reduce the work and difficulties encountered by the actors.
Methods
To design the system, two methods will be studied. Following this study, this system was designed based on method 2. SmartSysNephro is composed of a hardware part whose manipulations made by the user are visualized and assisted by the computer. This nephrostomy procedure that the user simulates is monitored by webcam. Using the data from this Intel Real Sense webcam, allowed to propose a CNN YOLO model.
Results
The results obtained show that the objectives set have been achieved globally. The SmartSysNephro system gives real time warning …
Nowadays, computerized nephrostomy techniques exist. Although relatively safe, several factors make it difficult for inexperienced users. A computer-assisted nephrostomy guidance system has been studied to increase the success rate of this intervention and reduce the work and difficulties encountered by the actors.
Methods
To design the system, two methods will be studied. Following this study, this system was designed based on method 2. SmartSysNephro is composed of a hardware part whose manipulations made by the user are visualized and assisted by the computer. This nephrostomy procedure that the user simulates is monitored by webcam. Using the data from this Intel Real Sense webcam, allowed to propose a CNN YOLO model.
Results
The results obtained show that the objectives set have been achieved globally. The SmartSysNephro system gives real time warning …
Fichtinger, Gabor; Holden, Matthew; Jannin, Pierre; Haegelen, Claire; Zhao, Yulong
Proficiency assessment system and method for deep brain stimulation (DBS) Journal Article
In: 2023.
@article{fichtinger2023k,
title = {Proficiency assessment system and method for deep brain stimulation (DBS)},
author = {Gabor Fichtinger and Matthew Holden and Pierre Jannin and Claire Haegelen and Yulong Zhao},
url = {https://patents.google.com/patent/US11756689B2/en},
year = {2023},
date = {2023-01-01},
urldate = {2023-01-01},
abstract = {A method for simulating a deep-brain stimulation in a computer-assisted platform that includes providing to a neurosurgeon, through a man-machine interface, visual information of a pre-operative situation, including a representation of a brain. The method also includes monitoring inputs of said neurosurgeon on the man-machine interface, until a trajectory is determined between an entry point and a target for the placement of an electrode. The method further includes comparing said trajectory to a set of previously-established trajectories for the pre-operative situation, so as to determine an overall measurement representative of a quality of the trajectory compared to the previously-established trajectories.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
A method for simulating a deep-brain stimulation in a computer-assisted platform that includes providing to a neurosurgeon, through a man-machine interface, visual information of a pre-operative situation, including a representation of a brain. The method also includes monitoring inputs of said neurosurgeon on the man-machine interface, until a trajectory is determined between an entry point and a target for the placement of an electrode. The method further includes comparing said trajectory to a set of previously-established trajectories for the pre-operative situation, so as to determine an overall measurement representative of a quality of the trajectory compared to the previously-established trajectories.
Tomalty, Diane; Giovannetti, Olivia; Velikonja, Leah; Munday, Jasica; Kaufmann, Martin; Iaboni, Natasha; Jamzad, Amoon; Rubino, Rachel; Fichtinger, Gabor; Mousavi, Parvin; Nicol, Christopher JB; Rudan, John F; Adams, Michael A
Molecular characterization of human peripheral nerves using desorption electrospray ionization mass spectrometry imaging Journal Article
In: Journal of Anatomy, vol. 243, iss. 5, pp. 758-769, 2023.
@article{fichtinger2023j,
title = {Molecular characterization of human peripheral nerves using desorption electrospray ionization mass spectrometry imaging},
author = {Diane Tomalty and Olivia Giovannetti and Leah Velikonja and Jasica Munday and Martin Kaufmann and Natasha Iaboni and Amoon Jamzad and Rachel Rubino and Gabor Fichtinger and Parvin Mousavi and Christopher JB Nicol and John F Rudan and Michael A Adams},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/joa.13909},
year = {2023},
date = {2023-01-01},
journal = {Journal of Anatomy},
volume = {243},
issue = {5},
pages = {758-769},
abstract = {Desorption electrospray ionization mass spectrometry imaging (DESI‐MSI) is a molecular imaging method that can be used to elucidate the small‐molecule composition of tissues and map their spatial information using two‐dimensional ion images. This technique has been used to investigate the molecular profiles of variety of tissues, including within the central nervous system, specifically the brain and spinal cord. To our knowledge, this technique has yet to be applied to tissues of the peripheral nervous system (PNS). Data generated from such analyses are expected to advance the characterization of these structures. The study aimed to: (i) establish whether DESI‐MSI can discriminate the molecular characteristics of peripheral nerves and distinguish them from surrounding tissues and (ii) assess whether different peripheral nerve subtypes are characterized by unique molecular profiles. Four different nerves for …},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Desorption electrospray ionization mass spectrometry imaging (DESI‐MSI) is a molecular imaging method that can be used to elucidate the small‐molecule composition of tissues and map their spatial information using two‐dimensional ion images. This technique has been used to investigate the molecular profiles of variety of tissues, including within the central nervous system, specifically the brain and spinal cord. To our knowledge, this technique has yet to be applied to tissues of the peripheral nervous system (PNS). Data generated from such analyses are expected to advance the characterization of these structures. The study aimed to: (i) establish whether DESI‐MSI can discriminate the molecular characteristics of peripheral nerves and distinguish them from surrounding tissues and (ii) assess whether different peripheral nerve subtypes are characterized by unique molecular profiles. Four different nerves for …
Srikanthan, Dilakshan; Kaufmann, Martin; Jamzad, Amoon; Syeda, Ayesha; Santilli, Alice; Sedghi, Alireza; Fichtinger, Gabor; Purzner, Jamie; Rudan, John; Purzner, Teresa; Mousavi, Parvin
Attention-based multi-instance learning for improved glioblastoma detection using mass spectrometry Journal Article
In: vol. 12466, pp. 248-253, 2023.
@article{fichtinger2023i,
title = {Attention-based multi-instance learning for improved glioblastoma detection using mass spectrometry},
author = {Dilakshan Srikanthan and Martin Kaufmann and Amoon Jamzad and Ayesha Syeda and Alice Santilli and Alireza Sedghi and Gabor Fichtinger and Jamie Purzner and John Rudan and Teresa Purzner and Parvin Mousavi},
url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12466/1246611/Attention-based-multi-instance-learning-for-improved-glioblastoma-detection-using/10.1117/12.2654436.short},
year = {2023},
date = {2023-01-01},
volume = {12466},
pages = {248-253},
publisher = {SPIE},
abstract = {Glioblastoma Multiforme (GBM) is the most common and most lethal primary brain tumor in adults with a five-year survival rate of 5%. The current standard of care and survival rate have remained largely unchanged due to the degree of difficulty in surgically removing these tumors, which plays a crucial role in survival, as better surgical resection leads to longer survival times. Thus, novel technologies need to be identified to improve resection accuracy. Our study features a curated database of GBM and normal brain tissue specimens, which we used to train and validate a multi-instance learning model for GBM detection via rapid evaporative ionization mass spectrometry. This method enables real-time tissue typing. The specimens were collected by a surgeon, reviewed by a pathologist, and sampled with an electrocautery device. The dataset comprised 276 normal tissue burns and 321 GBM tissue burns. Our multi …},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Glioblastoma Multiforme (GBM) is the most common and most lethal primary brain tumor in adults with a five-year survival rate of 5%. The current standard of care and survival rate have remained largely unchanged due to the degree of difficulty in surgically removing these tumors, which plays a crucial role in survival, as better surgical resection leads to longer survival times. Thus, novel technologies need to be identified to improve resection accuracy. Our study features a curated database of GBM and normal brain tissue specimens, which we used to train and validate a multi-instance learning model for GBM detection via rapid evaporative ionization mass spectrometry. This method enables real-time tissue typing. The specimens were collected by a surgeon, reviewed by a pathologist, and sampled with an electrocautery device. The dataset comprised 276 normal tissue burns and 321 GBM tissue burns. Our multi …
Szabó, Róbert Zsolt; Orosz, Gábor; Ungi, Tamás; Barr, Colton; Yeung, Chris; Incze, Roland; Fichtinger, Gabor; Gál, János; Haidegger, Tamás
Automation of lung ultrasound imaging and image processing for bedside diagnostic examinations Journal Article
In: pp. 000779-000784, 2023.
@article{fichtinger2023h,
title = {Automation of lung ultrasound imaging and image processing for bedside diagnostic examinations},
author = {Róbert Zsolt Szabó and Gábor Orosz and Tamás Ungi and Colton Barr and Chris Yeung and Roland Incze and Gabor Fichtinger and János Gál and Tamás Haidegger},
url = {https://ieeexplore.ieee.org/abstract/document/10158672/},
year = {2023},
date = {2023-01-01},
pages = {000779-000784},
publisher = {IEEE},
abstract = {The causes of acute respiratory failure can be difficult to identify for physicians. Experts can differentiate these causes using bedside lung ultrasound, but lung ultrasound has a considerable learning curve. We investigate if an automated decision-support system could help novices interpret lung ultrasound scans. The system utilizes medical ultrasound, data processing, and a neural network implementation to achieve this goal. The article details the steps taken in the data preparation, and the implementation of the neural network. The best model’s accuracy and error rate are presented, along with examples of its predictions. The paper concludes with an evaluation of the results, identification of limitations, and suggestions for future improvements.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The causes of acute respiratory failure can be difficult to identify for physicians. Experts can differentiate these causes using bedside lung ultrasound, but lung ultrasound has a considerable learning curve. We investigate if an automated decision-support system could help novices interpret lung ultrasound scans. The system utilizes medical ultrasound, data processing, and a neural network implementation to achieve this goal. The article details the steps taken in the data preparation, and the implementation of the neural network. The best model’s accuracy and error rate are presented, along with examples of its predictions. The paper concludes with an evaluation of the results, identification of limitations, and suggestions for future improvements.