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Automated Muscle Segmentation from Clinical CT using Bayesian U-Net for Personalized Musculoskeletal Modeling
[article]
2019
arXiv
pre-print
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We propose a method for automatic segmentation of individual muscles from a clinical CT. ...
The method uses Bayesian convolutional neural networks with the U-Net architecture, using Monte Carlo dropout that infers an uncertainty metric in addition to the segmentation label. ...
Therefore, our focus in this study is to develop an automated method of segmentation of individual muscles for personalization of the musculoskeletal model.
A. ...
arXiv:1907.08915v2
fatcat:ewaiugyn4vgb5gvjj2fk4h6oau
Table of contents
2020
IEEE Transactions on Medical Imaging
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Lediju Bell 1015 Automated Muscle Segmentation from Clinical CT Using Bayesian U-Net for Personalized Musculoskeletal .............................................................. M. Graham, F. ...
Eldar 1051 Comparison of Objective Image Quality Metrics to Expert Radiologists' Scoring of Diagnostic Quality of MR Images ....... A. Mason, J. Rioux, S. E. Clarke, A. Costa, M. Schmidt, V. ...
doi:10.1109/tmi.2020.2980809
fatcat:blpr4ksdlfgnffqvgqazbptfqu
Modality specific U-Net variants for biomedical image segmentation: A survey
[article]
2022
arXiv
pre-print
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image segmentation to address the automation in identification and detection of the target regions or sub-regions. ...
In recent studies, U-Net based approaches have illustrated state-of-the-art performance in different applications for the development of computer-aided diagnosis systems for early diagnosis and treatment ...
Acknowledgment We thank our institute, Indian Institute of Information Technology Allahabad (IIITA), India and Big Data Analytics (BDA) lab for allocating the necessary ...
arXiv:2107.04537v4
fatcat:m5oqea5q6vhbhkerjmejder3hu
2020 Index IEEE Transactions on Biomedical Engineering Vol. 67
2020
IEEE Transactions on Biomedical Engineering
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., A Time-Frequency Approach for Cerebral Embolic Load Monitoring; TBME April 2020 1007-1018 Imaduddin, S.M., Fanelli, A., Vonberg, F.W., Tasker, R.C., and Heldt, T., Pseudo-Bayesian Model-Based Noninvasive ...
, Pernus, F., Likar, B., and Spiclin, Z., Automated Cutting Plane Positioning for Intracranial Aneurysm Quantification; TBME Feb. 2020 577-587 Ji, D., see Shim, S., TBME Sept. 2020 2497-2506 Jia, S., ...
Iterative Label Denoising Network: Segmenting Male Pelvic Organs in CT From 3D Bounding Box Annotations. ...
doi:10.1109/tbme.2020.3048339
fatcat:y7zxxew27fgerapsnrhh54tm7y
CARS 2021: Computer Assisted Radiology and Surgery Proceedings of the 35th International Congress and Exhibition Munich, Germany, June 21–25, 2021
2021
International Journal of Computer Assisted Radiology and Surgery
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Acknowledgements This work has been funded by the research project PI18/00169 from Instituto de Salud Carlos III & FEDER funds. ...
We generated a stomach model from stomach region segmented from a CT volume. ...
The pelvic bone used for the phantom was segmented from the CT of a patient using 3D Slicer platform. ...
doi:10.1007/s11548-021-02375-4
pmid:34085172
fatcat:6d564hsv2fbybkhw4wvc7uuxcy
CARS 2020—Computer Assisted Radiology and Surgery Proceedings of the 34th International Congress and Exhibition, Munich, Germany, June 23–27, 2020
2020
International Journal of Computer Assisted Radiology and Surgery
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of the outstanding features of CARS is the personal (analogue) interaction of participants from different disciplines and cultures. ...
A hybrid (analogue and digital) CARS 2020 has therefore been envisaged to take place at the University Hospital in Munich, with a balanced combination of analogue/personal and digital presentations and ...
Acknowledgments This work was partly supported by a grant from Galgo Medical SL. We thank NVIDIA for the Titan X hardware grant that allowed us to process the images in a faster way. ...
doi:10.1007/s11548-020-02171-6
pmid:32514840
fatcat:lyhdb2zfpjcqbf4mmbunddwroq
2019 Index IEEE Transactions on Biomedical Engineering Vol. 66
2019
IEEE Transactions on Biomedical Engineering
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., +, TBME Feb. 2019 319-326 Sensitivity of Shoulder Musculoskeletal Model Predictions to Muscle-Tendon Properties. ...
., +, TBME Aug. 2019 2174-2181 Kinematics Sensitivity of Shoulder Musculoskeletal Model Predictions to Muscle-Tendon Properties. ...
doi:10.1109/tbme.2020.2964087
fatcat:mdfzsmdahnao5ccnuj232hycsm
Deep reinforcement learning in medical imaging: A literature review
[article]
2021
arXiv
pre-print
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We start with a comprehensive tutorial of DRL, including the latest model-free and model-based algorithms. ...
, personalized mobile health intervention, and computational model personalization. ...
Using the searched U-Net, the segmentation performances on the medical segmentation decathlon (MSD) challenges are better than those of the nnU-Net approach Isensee et al. (2018), which is considered as ...
arXiv:2103.05115v1
fatcat:ocr6kq7atnbhxazj7twvvhl5uy
CARS 2016—Computer Assisted Radiology and Surgery Proceedings of the 30th International Congress and Exhibition Heidelberg, Germany, June 21–25, 2016
2016
International Journal of Computer Assisted Radiology and Surgery
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We would like to thank the Spanish company BQ for the donation of the 3D printing hardware for clinical use. ...
Acknowledgements This study was supported in part by grants from the Ohio Department of Development (TVSF 15- ...
An experimental phantom model, which used a sheep's solid organs (liver, kidney, spleen and heart) and muscles, was prepared for validation of our segmentation method and volume computation of the semi-automated ...
doi:10.1007/s11548-016-1412-5
pmid:27206418
fatcat:uk5r46n2xvhedkfjzmeiweyneq
A Comparative Systematic Literature Review on Knee Bone Reports from MRI, X-rays and CT Scans Using Deep Learning and Machine Learning Methodologies
2020
Diagnostics
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The purpose of this research was to provide a "systematic literature review" of knee bone reports that are obtained by MRI, CT scans, and X-rays by using deep learning and machine learning techniques by ...
This research compares the deep learning methodologies for CT scan, MRI, and X-ray reports on knee bone, comparing the accuracy of each technique, which can be used for future development. ...
Researchers have demonstrated that u-net performed superiorly to the current cutting edge technique within clinically satisfactory runtimes. ...
doi:10.3390/diagnostics10080518
pmid:32722605
fatcat:mffkwokg4jdljkbyefvu7qmg54
SPR 2020
2020
Pediatric Radiology
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A convolutional neural network with the U-Net architecture was used to train the segmentation model. ...
Conclusions: The U-Net models trained on our datasets accurately segment the abdominal muscle on pediatric axial CT scans across the range of ages 0-18 years. ...
Clinical notes from the day of the procedure and longer term clinical follow up notes were used as a gold standard for complications. ...
doi:10.1007/s00247-020-04679-0
pmid:32435980
fatcat:y6da6d4blvaxlkus6w6zahpwlu
B - Scientific Sessions
2010
Insights into Imaging
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Methods and Materials: 20 patients with clinically suspected severe acute pancreatitis were referred for CT evaluation and imaged with a 320-slice CT unit within the first 24 hours after admission. ...
Purpose: To evaluate perfusion differences between oedemic and necrotic pancreatic tissue in patients with initial stage of acute pancreatitis using 320-slice dynamic volume CT. ...
A software running under Windows was developed for the automatic detection of left ventricular (LV) endocardial and epicardial contours on each MR image using a Bayesian flooding segmentation algorithm ...
doi:10.1007/s13244-010-0011-1
pmid:23099631
pmcid:PMC3534347
fatcat:yfnq3lgteja2lfjl66ivdfnoum
Abstracts
2022
Journal of neuroendocrinology
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Comparative biocomputational analysis of the splicing landscape across lung neuroendocrine neoplasms unveils a new actionable molecular layer . ...
Materials and methods: We conducted a retrospective analysis of patients (pts) with type 1 g-NETs treated from 2000 to oct 2021. Endoscopy and CT scan were used for staging. ...
Keywords: precision medicine, personalized treatment, neuroendocrine tumor, neuroendocrine carcinoma, molecular profile (F02) A systematic review of clinical prediction models for recurrence in patients ...
doi:10.1111/jne.13108
pmid:35253281
fatcat:rja6pngahbex5p6wqvxntlp3ty
15. Deutscher Wirbelsäulenkongress
2020
European spine journal
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Conclusion: We derived a fully automated planning tool for lumbosacral pedicle screws using AI. ...
A vertebra instancebased approach employing a state-of-the-art U-Net framework was developed and trained followed by internal 5-fold cross-validation. ...
The aim of this study is to identify risk factors for obese patients suffering from spondylodiscitis. ...
doi:10.1007/s00586-020-06630-1
pmid:33078266
fatcat:2e63m5xi7zfmrjjoxffwn5pq5m
Patient-Specific Inverse Modeling of In Vivo Cardiovascular Mechanics with Medical Image-Derived Kinematics as Input Data: Concepts, Methods, and Applications
2022
Applied Sciences
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Inverse modeling approaches in cardiovascular medicine are a collection of methodologies that can provide non-invasive patient-specific estimations of tissue properties, mechanical loads, and other mechanics-based ...
Herein, we review biomechanical modeling and simulation principles, methods of solving inverse problems, and techniques for image-based kinematic analysis. ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/app12083954
fatcat:so7cwudvyfgprigztufgw7we2e
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