Enhancement approach for liver lesion diagnosis using unenhanced CT images. Issue 8 (27th July 2018)

• Record Type: Journal Article
• Authors: Balagourouchetty, Lakshmipriya; Pragatheeswaran, Jayanthi K.; Pottakkat, Biju; Govindarajalou, Ramkumar
• Is Part Of: IET computer vision. Volume 12:Issue 8(2018)
• Page Start: 1078
• Page End: 1087
• Publication Date: 2018-07-27
• Subjects: computerised tomography -- kidney -- diseases -- image enhancement -- cancer -- tumours -- liver -- medical image processing; liver lesions -- unenhanced CT images -- enhanced images -- CT acquisition -- enhanced output -- lesion characterisation -- image enhancement approach -- liver lesion diagnosis -- hepatocellular carcinoma -- primary liver cancer -- liver-related pathologies -- contrast enhanced computed tomography images -- CECT imaging technology -- invasive technique -- intravenous contrast agent -- computed tomography acquisition -- diabetes -- kidney disorders -- novel enhancement technique; Computer vision -- Periodicals; Pattern recognition systems -- Periodicals; 006.37
• DOI: 10.1049/iet-cvi.2018.5265
• Languages: English
• ISSNs: 1751-9632

Abstract

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.