NDLI: Enhancement approach for liver lesion diagnosis using unenhanced CT images

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Enhancement approach for liver lesion diagnosis using unenhanced CT images

Content Provider	IET Digital Library
Author	Balagourouchetty, Lakshmipriya Pragatheeswaran, Jayanthi K. Pottakkat, Biju Govindarajalou, Ramkumar
Abstract	Hepatocellular carcinoma, the primary liver cancer and other liver-related pathologies are diagnosed with the help of contrast enhanced computed tomography (CECT) images. The CECT imaging technology is claimed to be an invasive technique, as the intravenous contrast agent injected prior to computed tomography (CT) acquisition is harmful and is not advised for patients with pre-existing diabetes and kidney disorders. This study presents a novel enhancement technique for the diagnosis of liver lesions from unenhanced CT images by means of fuzzy histogram equalisation in the non-sub-sampled contourlet transform domain followed by decorrelation stretching. The enhanced images obtained in this study substantiate that the proposed method improves the diagnostic value from the unenhanced CT images thereby providing an alternate painless solution for CT acquisition for the subset of patients mentioned above. Another major highlight of this work is the characterisation of lesions from the enhanced output for five different classes of pathology. The obtained results presented in this study demonstrate the potency of the proposed enhancement technique in achieving an appreciable performance in lesion characterisation. The images used for this research study have been obtained from Jawaharlal Institute of Medical Education and Research Puducherry, India.
Starting Page	1078
Ending Page	1087
Page Count	10
ISSN	17519632
Volume Number	12
e-ISSN	17519640
Issue Number	Issue 8, Dec (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-cvi/12/8
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-cvi.2018.5265
Journal	IET Computer Vision
Publisher Date	2018-07-12
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Biology And Medical Computing Biomedical Imaging/measurement Cancer CECT Imaging Technology Computed Tomography Acquisition Computer Vision And Image Processing Technique Computerised Tomography Contrast Enhanced Computed Tomography Image CT Acquisition Diabetes Diseases Enhanced Image Enhanced Output Hepatocellular Carcinoma Image Enhancement Image Enhancement Approach Intravenous Contrast Agent Invasive Technique Kidney Kidney Disorders Lesion Characterisation Liver Liver Lesion Diagnosis Liver Lesions Liver-related Pathologies Medical Image Processing Novel Enhancement Technique Optical, Image And Video Signal Processing Patient Diagnostic Method And Instrumentation Primary Liver Cancer Radiography And Computed Tomography Tumours Unenhanced CT Image X-Ray Technique X-Rays And Particle Beam
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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