[HTML][HTML] Imaging and cancer: a review

L Fass - Molecular oncology, 2008 - Elsevier
Multiple biomedical imaging techniques are used in all phases of cancer management.
Imaging forms an essential part of cancer clinical protocols and is able to furnish …

The second ESGAR consensus statement on CT colonography

E Neri, S Halligan, M Hellström, P Lefere, T Mang… - European …, 2013 - Springer
Objective To update quality standards for CT colonography based on consensus among
opinion leaders within the European Society of Gastrointestinal and Abdominal Radiology …

Who goes first? Influences of human-AI workflow on decision making in clinical imaging

R Fogliato, S Chappidi, M Lungren, P Fisher… - Proceedings of the …, 2022 - dl.acm.org
Details of the designs and mechanisms in support of human-AI collaboration must be
considered in the real-world fielding of AI technologies. A critical aspect of interaction design …

Evaluation of computer‐aided detection and diagnosis systemsa)

N Petrick, B Sahiner, SG Armato III, A Bert… - Medical …, 2013 - Wiley Online Library
Computer‐aided detection and diagnosis (CAD) systems are increasingly being used as an
aid by clinicians for detection and interpretation of diseases. Computer‐aided detection …

Effect of CAD on radiologists' detection of lung nodules on thoracic CT scans: analysis of an observer performance study by nodule size

B Sahiner, HP Chan, LM Hadjiiski, PN Cascade… - Academic radiology, 2009 - Elsevier
RATIONALE AND OBJECTIVES: To retrospectively investigate the effect of a computer-
aided detection (CAD) system on radiologists' performance for detecting small pulmonary …

Progress in fully automated abdominal CT interpretation

RM Summers - American Journal of Roentgenology, 2016 - Am Roentgen Ray Soc
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 …

Performance and reading time of lung nodule identification on multidetector CT with or without an artificial intelligence-powered computer-aided detection system

HH Hsu, KH Ko, YC Chou, YC Wu, SH Chiu… - Clinical Radiology, 2021 - Elsevier
AIM To compare the performance and reading time of different readers using automatic
artificial intelligence (AI)-powered computer-aided detection (CAD) to detect lung nodules in …

Distributed human intelligence for colonic polyp classification in computer-aided detection for CT colonography

TB Nguyen, S Wang, V Anugu, N Rose, M McKenna… - Radiology, 2012 - pubs.rsna.org
Purpose To assess the diagnostic performance of distributed human intelligence for the
classification of polyp candidates identified with computer-aided detection (CAD) for …

Effect of computer-aided detection for CT colonography in a multireader, multicase trial

AH Dachman, NA Obuchowski, JW Hoffmeister… - Radiology, 2010 - pubs.rsna.org
Purpose To assess the effect of using computer-aided detection (CAD) in second-read mode
on readers' accuracy in interpreting computed tomographic (CT) colonographic images …

Computer-aided detection of brain metastasis on 3D MR imaging: Observer performance study

L Sunwoo, YJ Kim, SH Choi, KG Kim, JH Kang… - PLoS …, 2017 - journals.plos.org
Purpose To assess the effect of computer-aided detection (CAD) of brain metastasis (BM) on
radiologists' diagnostic performance in interpreting three-dimensional brain magnetic …