Literature DB >> 27101207

Progress in Fully Automated Abdominal CT Interpretation.

Ronald M Summers1.   

Abstract

OBJECTIVE: Automated analysis of abdominal CT has advanced markedly over just the last few years. Fully automated assessment of organs, lymph nodes, adipose tissue, muscle, bowel, spine, and tumors are some examples where tremendous progress has been made. Computer-aided detection of lesions has also improved dramatically.
CONCLUSION: This article reviews the progress and provides insights into what is in store in the near future for automated analysis for abdominal CT, ultimately leading to fully automated interpretation.

Entities:  

Keywords:  CT; computer-aided detection; image processing; segmentation; volumetrics

Mesh:

Year:  2016        PMID: 27101207      PMCID: PMC4919161          DOI: 10.2214/AJR.15.15996

Source DB:  PubMed          Journal:  AJR Am J Roentgenol        ISSN: 0361-803X            Impact factor:   3.959


  128 in total

1.  A statistical 3-D pattern processing method for computer-aided detection of polyps in CT colonography.

Authors:  S B Göktürk; C Tomasi; B Acar; C F Beaulieu; D S Paik; R B Jeffrey; J Yee; S Napel
Journal:  IEEE Trans Med Imaging       Date:  2001-12       Impact factor: 10.048

2.  Visceral fat analysis at CT colonography.

Authors:  Kristina T Johnson; William S Harmsen; Paul J Limburg; Michael J Carston; Charles D Johnson
Journal:  Acad Radiol       Date:  2006-08       Impact factor: 3.173

3.  Computed tomographic virtual colonoscopy computer-aided polyp detection in a screening population.

Authors:  Ronald M Summers; Jianhua Yao; Perry J Pickhardt; Marek Franaszek; Ingmar Bitter; Daniel Brickman; Vamsi Krishna; J Richard Choi
Journal:  Gastroenterology       Date:  2005-12       Impact factor: 22.682

4.  Automated segmentation and quantification of liver and spleen from CT images using normalized probabilistic atlases and enhancement estimation.

Authors:  Marius George Linguraru; Jesse K Sandberg; Zhixi Li; Furhawn Shah; Ronald M Summers
Journal:  Med Phys       Date:  2010-02       Impact factor: 4.071

5.  Computer-aided detection of exophytic renal lesions on non-contrast CT images.

Authors:  Jianfei Liu; Shijun Wang; Marius George Linguraru; Jianhua Yao; Ronald M Summers
Journal:  Med Image Anal       Date:  2014-08-15       Impact factor: 8.545

Review 6.  Machine learning and radiology.

Authors:  Shijun Wang; Ronald M Summers
Journal:  Med Image Anal       Date:  2012-02-23       Impact factor: 8.545

7.  Treatment Response Assessment for Bladder Cancer on CT Based on Computerized Volume Analysis, World Health Organization Criteria, and RECIST.

Authors:  Lubomir Hadjiiski; Alon Z Weizer; Ajjai Alva; Elaine M Caoili; Richard H Cohan; Kenny Cha; Heang-Ping Chan
Journal:  AJR Am J Roentgenol       Date:  2015-08       Impact factor: 3.959

8.  The three column spine and its significance in the classification of acute thoracolumbar spinal injuries.

Authors:  F Denis
Journal:  Spine (Phila Pa 1976)       Date:  1983 Nov-Dec       Impact factor: 3.468

9.  Teniae coli-based circumferential localization system for CT colonography: feasibility study.

Authors:  Adam Huang; Dave A Roy; Ronald M Summers; Marek Franaszek; Nicholas Petrick; J Richard Choi; Perry J Pickhardt
Journal:  Radiology       Date:  2007-05       Impact factor: 11.105

10.  Associations among pericolonic fat, visceral fat, and colorectal polyps on CT colonography.

Authors:  Jiamin Liu; Sanket Pattanaik; Jianhua Yao; Andrew J Dwyer; Perry J Pickhardt; J Richard Choi; Ronald M Summers
Journal:  Obesity (Silver Spring)       Date:  2014-12-31       Impact factor: 5.002

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  19 in total

Review 1.  Advanced imaging techniques for chronic pancreatitis.

Authors:  Anushri Parakh; Temel Tirkes
Journal:  Abdom Radiol (NY)       Date:  2020-05

2.  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

Review 3.  Demystification of AI-driven medical image interpretation: past, present and future.

Authors:  Peter Savadjiev; Jaron Chong; Anthony Dohan; Maria Vakalopoulou; Caroline Reinhold; Nikos Paragios; Benoit Gallix
Journal:  Eur Radiol       Date:  2018-08-13       Impact factor: 5.315

Review 4.  Sensor, Signal, and Imaging Informatics.

Authors:  W Hsu; S Park; Charles E Kahn
Journal:  Yearb Med Inform       Date:  2017-09-11

5.  Deep Learning Lends a Hand to Pediatric Radiology.

Authors:  Ronald M Summers
Journal:  Radiology       Date:  2018-04       Impact factor: 11.105

6.  Holistic segmentation of the lung in cine MRI.

Authors:  William Kovacs; Nathan Hsieh; Holger Roth; Chioma Nnamdi-Emeratom; W Patricia Bandettini; Andrew Arai; Ami Mankodi; Ronald M Summers; Jianhua Yao
Journal:  J Med Imaging (Bellingham)       Date:  2017-11-30

7.  Machine Learning for Automatic Paraspinous Muscle Area and Attenuation Measures on Low-Dose Chest CT Scans.

Authors:  Ryan Barnard; Josh Tan; Brandon Roller; Caroline Chiles; Ashley A Weaver; Robert D Boutin; Stephen B Kritchevsky; Leon Lenchik
Journal:  Acad Radiol       Date:  2019-07-17       Impact factor: 3.173

8.  Automated CT and MRI Liver Segmentation and Biometry Using a Generalized Convolutional Neural Network.

Authors:  Kang Wang; Adrija Mamidipalli; Tara Retson; Naeim Bahrami; Kyle Hasenstab; Kevin Blansit; Emily Bass; Timoteo Delgado; Guilherme Cunha; Michael S Middleton; Rohit Loomba; Brent A Neuschwander-Tetri; Claude B Sirlin; Albert Hsiao
Journal:  Radiol Artif Intell       Date:  2019-03-27

Review 9.  Opportunistic Screening at Abdominal CT: Use of Automated Body Composition Biomarkers for Added Cardiometabolic Value.

Authors:  Perry J Pickhardt; Peter M Graffy; Alberto A Perez; Meghan G Lubner; Daniel C Elton; Ronald M Summers
Journal:  Radiographics       Date:  2021 Mar-Apr       Impact factor: 5.333

10.  Automated Detection of Pancreatic Cystic Lesions on CT Using Deep Learning.

Authors:  Lorraine Abel; Jakob Wasserthal; Thomas Weikert; Alexander W Sauter; Ivan Nesic; Marko Obradovic; Shan Yang; Sebastian Manneck; Carl Glessgen; Johanna M Ospel; Bram Stieltjes; Daniel T Boll; Björn Friebe
Journal:  Diagnostics (Basel)       Date:  2021-05-19
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