Literature DB >> 26415164

Body Composition Assessment in Axial CT Images Using FEM-Based Automatic Segmentation of Skeletal Muscle.

Karteek Popuri, Dana Cobzas, Nina Esfandiari, Vickie Baracos, Martin Jägersand.   

Abstract

The proportions of muscle and fat tissues in the human body, referred to as body composition is a vital measurement for cancer patients. Body composition has been recently linked to patient survival and the onset/recurrence of several types of cancers in numerous cancer research studies. This paper introduces a fully automatic framework for the segmentation of muscle and fat tissues from CT images to estimate body composition. We developed a novel finite element method (FEM) deformable model that incorporates a priori shape information via a statistical deformation model (SDM) within the template-based segmentation framework. The proposed method was validated on 1000 abdominal and 530 thoracic CT images and we obtained very good segmentation results with Jaccard scores in excess of 90% for both the muscle and fat regions.

Entities:  

Mesh:

Year:  2015        PMID: 26415164     DOI: 10.1109/TMI.2015.2479252

Source DB:  PubMed          Journal:  IEEE Trans Med Imaging        ISSN: 0278-0062            Impact factor:   10.048


  41 in total

1.  Survivorship in immune therapy: Assessing toxicities, body composition and health-related quality of life among long-term survivors treated with antibodies to programmed death-1 receptor and its ligand.

Authors:  James Randall Patrinely; Arissa C Young; Henry Quach; Grant R Williams; Fei Ye; Run Fan; Leora Horn; Kathryn E Beckermann; Erin A Gillaspie; Jeffrey A Sosman; Debra L Friedman; Javid J Moslehi; Douglas B Johnson
Journal:  Eur J Cancer       Date:  2020-06-27       Impact factor: 9.162

2.  Muscle segmentation in axial computed tomography (CT) images at the lumbar (L3) and thoracic (T4) levels for body composition analysis.

Authors:  Setareh Dabiri; Karteek Popuri; Elizabeth M Cespedes Feliciano; Bette J Caan; Vickie E Baracos; Mirza Faisal Beg
Journal:  Comput Med Imaging Graph       Date:  2019-05-09       Impact factor: 4.790

3.  Change in Skeletal Muscle Following Resection of Stage I-III Colorectal Cancer is Predictive of Poor Survival: A Cohort Study.

Authors:  Jessica J Hopkins; Rebecca Reif; David Bigam; Vickie E Baracos; Dean T Eurich; Michael M Sawyer
Journal:  World J Surg       Date:  2019-10       Impact factor: 3.352

4.  Body Composition as a Predictor of Toxicity in Patients Receiving Anthracycline and Taxane-Based Chemotherapy for Early-Stage Breast Cancer.

Authors:  Shlomit Strulov Shachar; Allison M Deal; Marc Weinberg; Grant R Williams; Kirsten A Nyrop; Karteek Popuri; Seul Ki Choi; Hyman B Muss
Journal:  Clin Cancer Res       Date:  2017-01-31       Impact factor: 12.531

5.  Automated muscle segmentation from CT images of the hip and thigh using a hierarchical multi-atlas method.

Authors:  Futoshi Yokota; Yoshito Otake; Masaki Takao; Takeshi Ogawa; Toshiyuki Okada; Nobuhiko Sugano; Yoshinobu Sato
Journal:  Int J Comput Assist Radiol Surg       Date:  2018-04-06       Impact factor: 2.924

6.  Adipose Tissue Distribution and Cardiovascular Disease Risk Among Breast Cancer Survivors.

Authors:  Elizabeth M Cespedes Feliciano; Wendy Y Chen; Patrick T Bradshaw; Carla M Prado; Stacey Alexeeff; Kathleen B Albers; Adrienne L Castillo; Bette J Caan
Journal:  J Clin Oncol       Date:  2019-08-01       Impact factor: 44.544

7.  Automated Segmentation of Tissues Using CT and MRI: A Systematic Review.

Authors:  Leon Lenchik; Laura Heacock; Ashley A Weaver; Robert D Boutin; Tessa S Cook; Jason Itri; Christopher G Filippi; Rao P Gullapalli; James Lee; Marianna Zagurovskaya; Tara Retson; Kendra Godwin; Joey Nicholson; Ponnada A Narayana
Journal:  Acad Radiol       Date:  2019-08-10       Impact factor: 3.173

8.  Fully automatic segmentation of paraspinal muscles from 3D torso CT images via multi-scale iterative random forest classifications.

Authors:  Naoki Kamiya; Jing Li; Masanori Kume; Hiroshi Fujita; Dinggang Shen; Guoyan Zheng
Journal:  Int J Comput Assist Radiol Surg       Date:  2018-09-01       Impact factor: 2.924

9.  Automated body composition analysis of clinically acquired computed tomography scans using neural networks.

Authors:  Michael T Paris; Puneeta Tandon; Daren K Heyland; Helena Furberg; Tahira Premji; Gavin Low; Marina Mourtzakis
Journal:  Clin Nutr       Date:  2020-01-22       Impact factor: 7.324

10.  Deep learning method for localization and segmentation of abdominal CT.

Authors:  Setareh Dabiri; Karteek Popuri; Cydney Ma; Vincent Chow; Elizabeth M Cespedes Feliciano; Bette J Caan; Vickie E Baracos; Mirza Faisal Beg
Journal:  Comput Med Imaging Graph       Date:  2020-08-14       Impact factor: 4.790

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.