Paper Info
Title
Vision-based personalized Wireless Capsule Endoscopy for smart healthcare: Taxonomy, literature review, opportunities and challenges
Abstract
Wireless Capsule Endoscopy (WCE) is a patient-friendly approach for digestive tract monitoring to support medical experts towards identifying any anomaly inside human’s Gastrointestinal (GI) tract. The automatic recognition of such type of abnormalities is essential for early diagnosis and time saving. To this end, several computer aided diagnosis (CAD) methods have been proposed in the literature for automatic abnormal region segmentation, summarization, classification, and personalization in WCE videos. In this work, we provide a detailed review of computer vision-based methods for WCE videos analysis. Firstly, all the major domains of WCE video analytics with their generic flow are identified. Secondly, we comprehensively review WCE video analysis methods and surveys with their pros and cons presented to date. In addition, this paper reviews several representative public datasets used for the performance assessment of WCE techniques and methods. Finally, the most important aspect of this survey is the identification of several research trends and open issues in different domains of WCE, with an emphasis placed on future research directions towards smarter healthcare and personalization.
Year
DOI
Venue
2020
10.1016/j.future.2020.06.048
Future Generation Computer Systems
Keywords
DocType
Volume
Artificial intelligence,Biomedical data analysis,Data science,Health monitoring,Smart healthcare,Wireless Capsule Endoscopy
Journal
113
ISSN
Citations 
PageRank 
0167-739X
2
0.35
References 
Authors
76
5
Name
Order
Citations
PageRank
Khan Muhammad198667.67
Salman Khan238741.05
Neeraj Kumar32889236.13
Javier Del Ser471287.90
Seyedali Mirjalili53949140.80