224 related articles for article (PubMed ID: 31822001)
1. Body Composition Analysis of Computed Tomography Scans in Clinical Populations: The Role of Deep Learning.
Paris MT
Lifestyle Genom; 2020; 13(1):28-31. PubMed ID: 31822001
[TBL] [Abstract][Full Text] [Related]
2. Automated body composition analysis of clinically acquired computed tomography scans using neural networks.
Paris MT; Tandon P; Heyland DK; Furberg H; Premji T; Low G; Mourtzakis M
Clin Nutr; 2020 Oct; 39(10):3049-3055. PubMed ID: 32007318
[TBL] [Abstract][Full Text] [Related]
3. Evaluating body composition by combining quantitative spectral detector computed tomography and deep learning-based image segmentation.
Zopfs D; Bousabarah K; Lennartz S; Santos DPD; Schlaak M; Theurich S; Reimer RP; Maintz D; Haneder S; Große Hokamp N
Eur J Radiol; 2020 Sep; 130():109153. PubMed ID: 32717577
[TBL] [Abstract][Full Text] [Related]
4. Clinical evaluation of automated segmentation for body composition analysis on abdominal L3 CT slices in polytrauma patients.
Ackermans LLGC; Volmer L; Timmermans QMMA; Brecheisen R; Damink SMWO; Dekker A; Loeffen D; Poeze M; Blokhuis TJ; Wee L; Ten Bosch JA
Injury; 2022 Nov; 53 Suppl 3():S30-S41. PubMed ID: 35680433
[TBL] [Abstract][Full Text] [Related]
5. Fully Automated Segmentation of Connective Tissue Compartments for CT-Based Body Composition Analysis: A Deep Learning Approach.
Nowak S; Faron A; Luetkens JA; Geißler HL; Praktiknjo M; Block W; Thomas D; Sprinkart AM
Invest Radiol; 2020 Jun; 55(6):357-366. PubMed ID: 32369318
[TBL] [Abstract][Full Text] [Related]
6. Evaluation of automated computed tomography segmentation to assess body composition and mortality associations in cancer patients.
Cespedes Feliciano EM; Popuri K; Cobzas D; Baracos VE; Beg MF; Khan AD; Ma C; Chow V; Prado CM; Xiao J; Liu V; Chen WY; Meyerhardt J; Albers KB; Caan BJ
J Cachexia Sarcopenia Muscle; 2020 Oct; 11(5):1258-1269. PubMed ID: 32314543
[TBL] [Abstract][Full Text] [Related]
7. Measuring Abdominal Circumference and Skeletal Muscle From a Single Cross-Sectional Computed Tomography Image: A Step-by-Step Guide for Clinicians Using National Institutes of Health ImageJ.
Gomez-Perez SL; Haus JM; Sheean P; Patel B; Mar W; Chaudhry V; McKeever L; Braunschweig C
JPEN J Parenter Enteral Nutr; 2016 Mar; 40(3):308-18. PubMed ID: 26392166
[TBL] [Abstract][Full Text] [Related]
8. Deep Learning Automated Segmentation for Muscle and Adipose Tissue from Abdominal Computed Tomography in Polytrauma Patients.
Ackermans LLGC; Volmer L; Wee L; Brecheisen R; Sánchez-González P; Seiffert AP; Gómez EJ; Dekker A; Ten Bosch JA; Olde Damink SMW; Blokhuis TJ
Sensors (Basel); 2021 Mar; 21(6):. PubMed ID: 33809710
[TBL] [Abstract][Full Text] [Related]
9. Development of a fully automatic deep learning system for L3 selection and body composition assessment on computed tomography.
Ha J; Park T; Kim HK; Shin Y; Ko Y; Kim DW; Sung YS; Lee J; Ham SJ; Khang S; Jeong H; Koo K; Lee J; Kim KW
Sci Rep; 2021 Nov; 11(1):21656. PubMed ID: 34737340
[TBL] [Abstract][Full Text] [Related]
10. Deep neural network for automatic volumetric segmentation of whole-body CT images for body composition assessment.
Lee YS; Hong N; Witanto JN; Choi YR; Park J; Decazes P; Eude F; Kim CO; Chang Kim H; Goo JM; Rhee Y; Yoon SH
Clin Nutr; 2021 Aug; 40(8):5038-5046. PubMed ID: 34365038
[TBL] [Abstract][Full Text] [Related]
11. Population-Scale CT-based Body Composition Analysis of a Large Outpatient Population Using Deep Learning to Derive Age-, Sex-, and Race-specific Reference Curves.
Magudia K; Bridge CP; Bay CP; Babic A; Fintelmann FJ; Troschel FM; Miskin N; Wrobel WC; Brais LK; Andriole KP; Wolpin BM; Rosenthal MH
Radiology; 2021 Feb; 298(2):319-329. PubMed ID: 33231527
[TBL] [Abstract][Full Text] [Related]
12. End-to-end automated body composition analyses with integrated quality control for opportunistic assessment of sarcopenia in CT.
Nowak S; Theis M; Wichtmann BD; Faron A; Froelich MF; Tollens F; Geißler HL; Block W; Luetkens JA; Attenberger UI; Sprinkart AM
Eur Radiol; 2022 May; 32(5):3142-3151. PubMed ID: 34595539
[TBL] [Abstract][Full Text] [Related]
13. An Effective CNN Method for Fully Automated Segmenting Subcutaneous and Visceral Adipose Tissue on CT Scans.
Wang Z; Meng Y; Weng F; Chen Y; Lu F; Liu X; Hou M; Zhang J
Ann Biomed Eng; 2020 Jan; 48(1):312-328. PubMed ID: 31451989
[TBL] [Abstract][Full Text] [Related]
14. Reliability and validity of the new VikingSlice software for computed tomography body composition analysis.
Ozola-Zālīte I; Mark EB; Gudauskas T; Lyadov V; Olesen SS; Drewes AM; Pukitis A; Frokjær JB
Eur J Clin Nutr; 2019 Jan; 73(1):54-61. PubMed ID: 29662230
[TBL] [Abstract][Full Text] [Related]
15. Concordance of Computed Tomography Regional Body Composition Analysis Using a Fully Automated Open-Source Neural Network versus a Reference Semi-Automated Program with Manual Correction.
Gomez-Perez SL; Zhang Y; Byrne C; Wakefield C; Geesey T; Sclamberg J; Peterson S
Sensors (Basel); 2022 Apr; 22(9):. PubMed ID: 35591047
[TBL] [Abstract][Full Text] [Related]
16. Deep learning for automated segmentation of pelvic muscles, fat, and bone from CT studies for body composition assessment.
Hemke R; Buckless CG; Tsao A; Wang B; Torriani M
Skeletal Radiol; 2020 Mar; 49(3):387-395. PubMed ID: 31396667
[TBL] [Abstract][Full Text] [Related]
17. Development and Validation of a Deep Learning System for Segmentation of Abdominal Muscle and Fat on Computed Tomography.
Park HJ; Shin Y; Park J; Kim H; Lee IS; Seo DW; Huh J; Lee TY; Park T; Lee J; Kim KW
Korean J Radiol; 2020 Jan; 21(1):88-100. PubMed ID: 31920032
[TBL] [Abstract][Full Text] [Related]
18. Automated analysis of liver fat, muscle and adipose tissue distribution from CT suitable for large-scale studies.
Kullberg J; Hedström A; Brandberg J; Strand R; Johansson L; Bergström G; Ahlström H
Sci Rep; 2017 Sep; 7(1):10425. PubMed ID: 28874743
[TBL] [Abstract][Full Text] [Related]
19. Deep Learning for Quantification of Epicardial and Thoracic Adipose Tissue From Non-Contrast CT.
Commandeur F; Goeller M; Betancur J; Cadet S; Doris M; Chen X; Berman DS; Slomka PJ; Tamarappoo BK; Dey D
IEEE Trans Med Imaging; 2018 Aug; 37(8):1835-1846. PubMed ID: 29994362
[TBL] [Abstract][Full Text] [Related]
20. Quantification of body-torso-wide tissue composition on low-dose CT images via automatic anatomy recognition.
Liu T; Udupa JK; Miao Q; Tong Y; Torigian DA
Med Phys; 2019 Mar; 46(3):1272-1285. PubMed ID: 30614020
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
