End‐to‐end domain knowledge‐assisted automatic diagnosis of idiopathic pulmonary fibrosis (IPF) using computed tomography (CT)

• Published in: Medical physics (Lancaster) Vol. 48; no. 5; pp. 2458 - 2467
• Main Authors: Yu, Wenxi, Zhou, Hua, Goldin, Jonathan G., Wong, Weng Kee, Kim, Grace Hyun J.
• Format: Journal Article
• Language: English
• Published: United States 01.05.2021
• Subjects: computed tomography; deep learning; Humans; idiopathic pulmonary fibrosis (IPF); Idiopathic Pulmonary Fibrosis - diagnostic imaging; Lung Diseases, Interstitial; optimal design; Prospective Studies; Retrospective Studies; Tomography, X-Ray Computed; computed tomography; optimal design; deep learning; idiopathic pulmonary fibrosis (IPF)

Purpose Domain knowledge (DK) acquired from prior studies is important for medical diagnosis. This paper leverages the population‐level DK using an optimality design criterion to train a deep learning model in an end‐to‐end manner. In this study, the problem of interest is at the patient level to di...