Computer-aided diagnosis of renal lesions in CT images: A comprehensive survey and future prospects. (July 2019)

• Record Type: Journal Article
• Authors: Kaur, Ravinder; Juneja, Mamta; Mandal, AK
• Is Part Of: Computers & electrical engineering. Volume 77(2019)
• Page Start: 423
• Page End: 434
• Publication Date: 2019-07
• Subjects: CT images -- Computer-aided diagnosis -- Renal lesion -- Segmentation -- Classification; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2018.07.024
• Languages: English
• ISSNs: 0045-7906

Abstract

Abstract: Computer-Aided Diagnosis (CADx) systems can improve the investigative proficiencies of clinicians and minimize the time required for carrying out the accurate diagnosis. However, the limited availability of several sophisticated easy-to-use CADx systems has led to great concern regarding the non-invasive, accurate and timely diagnosis of diseases. In the literature, inadequate work has been done for the development of CADx systems for renal lesions. This article aims to present a comprehensive and scrutinizing bibliography addressing the published literature in this field with primary focus on pre-processing, segmentation and classification of renal lesions in Computed Tomography (CT) images. The main objective is to provide an overview for the researchers who are beginners in this field and are not well equipped to understand its complete technical aspects. Furthermore, it highlights some of the open challenges found in the literature that require the attention of future researchers to explore new avenues in this domain.