CaltechAUTHORS
  A Caltech Library Service

Diagnostic Image Quality Assessment and Classification in Medical Imaging: Opportunities and Challenges

Ma, Jeffrey J. and Nakarmi, Ukash and Kin, Cedric Yue Sik and Sandino, Christopher M. and Cheng, Joseph Y. and Syed, Ali B. and Weir, Peter and Pauly, John M. and Vasanawala, Shreyas S. (2020) Diagnostic Image Quality Assessment and Classification in Medical Imaging: Opportunities and Challenges. In: 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI). IEEE , Piscataway, NJ, pp. 337-340. ISBN 9781538693308. https://resolver.caltech.edu/CaltechAUTHORS:20201030-080636957

[img] PDF - Submitted Version
See Usage Policy.

1MB

Use this Persistent URL to link to this item: https://resolver.caltech.edu/CaltechAUTHORS:20201030-080636957

Abstract

Magnetic Resonance Imaging (MRI) suffers from several artifacts, the most common of which are motion artifacts. These artifacts often yield images that are of non-diagnostic quality. To detect such artifacts, images are prospectively evaluated by experts for their diagnostic quality, which necessitates patient-revisits and rescans whenever non-diagnostic quality scans are encountered. This motivates the need to develop an automated framework capable of accessing medical image quality and detecting diagnostic and non-diagnostic images. In this paper, we explore several convolutional neural network-based frameworks for medical image quality assessment and investigate several challenges therein.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
https://doi.org/10.1109/isbi45749.2020.9098735DOIArticle
https://arxiv.org/abs/1912.02907arXivDiscussion Paper
ORCID:
AuthorORCID
Weir, Peter0000-0003-3111-7829
Additional Information:© 2020 IEEE. This work is supported in part by the NIH R01EB009690 and NIH R01 EB026136 grants, by GE Healthcare, and by the Caltech SURF program.
Funders:
Funding AgencyGrant Number
NIHR01 EB009690
NIHR01 EB026136
GE HealthcareUNSPECIFIED
Caltech Summer Undergraduate Research Fellowship (SURF)UNSPECIFIED
Subject Keywords:Image quality, deep learning, medical imaging
DOI:10.1109/isbi45749.2020.9098735
Record Number:CaltechAUTHORS:20201030-080636957
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20201030-080636957
Official Citation:J. J. Ma et al., "Diagnostic Image Quality Assessment and Classification in Medical Imaging: Opportunities and Challenges," 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI), Iowa City, IA, USA, 2020, pp. 337-340, doi: 10.1109/ISBI45749.2020.9098735
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:106350
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:30 Oct 2020 15:41
Last Modified:16 Nov 2021 18:53

Repository Staff Only: item control page