Notable CAD papers published in Medical Physics - Virtual Issue Introduction
Channel: Journal Video Highlights
Date: 2021-01-05

Notable Papers in Computer-aided Detection & Diagnosis Published in MEDICAL PHYSICS by Heather M. Whitney and Maryellen L. Giger

Virtual Issue available: https://aapm.onlinelibrary.wiley.com/doi/toc/10.1002/(ISSN)2473-4209.notable-cad-papers

This latest virtual article compiles and reflectively reviews the beginning and growth of computer-aided detection/diagnosis (CAD) as told through the pages of MEDICAL PHYSICS, thirty-one articles in all.  The virtual article starts with two major MEDICAL PHYSICS review papers on computer aided detection and computer aided diagnosis. Each of these works has been influential in describing the state of the field and informing those who have entered it during the past decade.

Computer-aided detection is a localization task, often developed for screening programs in which most patients present without symptoms of the disease under surveillance, such as breast cancer screening through screening mammography. The journal MEDICAL PHYSICS has published several seminal papers on the topic, starting in the 1980s.  Similarly, many important papers in computer-aided diagnosis are also presented from the journal.

The collection also highlights several papers that illustrate various important methods in the conduction of CAD research, development, evaluation, and translation. Readers who are new to CAD may be surprised at the inclusion of methods that are familiar from the field of artificial intelligence (AI) at large. It should be noted that while AI refers to the algorithm, CAD refers to how the AI is implemented by the end user. The methods with which AI developers select features, and design and train classifiers in computer aided detection and diagnosis, is crucial for appropriate CAD system design and ultimate use. Best practices in the relevant AI methods have been the subject of study since the inception of the field of CAD, as demonstrated by publications in MEDICAL PHYSICS. Seven of the papers described here provide insight into both feature selection and classifier design on a number of different fronts.  The 8th paper illustrates the importance of databases in AI research, and the 9th paper summarizes the need for robust evaluation methods in order to enable translation of developed AI methods.

In summary, a vast amount of CAD research, often now referred to as AI, has been conducted over the past 35 years, with many findings having been published in MEDICAL PHYSICS. With many advances in computing power, increased availability of databases, and growing complexity of algorithms, AI is rapidly expanding across clinical tasks, imaging modalities, disease types, and clinical implementation.  Aspects of development, training, testing, and translation of AI have remained to ensure generalizability and reproducibility.

Thank you for the opportunity to present to you these notable papers in CAD from the journal MEDICAL PHYSICS. We hope the collection is both informational and inspirational.Notable Papers in Computer-aided Detection & Diagnosis Published in MEDICAL PHYSICS