Citation

Ang, Jinger and Sim, Kok Swee and Tan, Shing Chiang (2026) Enhanced Diagnostic Visualization Application through Advanced Histogram Equalization Techniques in DICOM Image Processing for Brain Lesion Detection. International Journal on Advanced Science, Engineering and Information Technology, 16 (2). pp. 600-610. ISSN 2088-5334

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Abstract

The Enhanced Diagnostic Visualization (EDV) system is an advanced medical imaging platform designed to improve neuroimaging analysis through efficient image loading, automated contrast enhancement, and interactive visualization tools. The proposed Graphical User Interface (GUI) is developed specifically to enhance the visualization of brain lesion images. It supports batch loading of Digital Imaging and Communications in Medicine (DICOM) files, enabling seamless management of large datasets from various imaging modalities such as MRI and CT scans. A feature named Dynamic Scan Layer Navigation (DSLN) Mechanism is introduced to facilitate loading and navigation through a series of brain scans, providing a detailed examination of brain structures across different axial planes and aiding the accurate identification of neurological conditions. A key feature of the EDV system is its automated contrast enhancement and visualization engine, which applies multiple histogram equalization techniques, including Dualistic Sub-Image Histogram Equalization (DSIHE), Exponential Logarithmic Histogram Equalization (ELEHE), Exponential Logarithmic Adaptive Histogram Equalization (ELEAHE), and Contrast Limited Adaptive Histogram Equalization (CLAHE). Additionally, colorization methods are also included to enhance grayscale medical images, improving the differentiation of tissue structures and anomalies. By generating precomputed multi-method contrast views, the system enables healthcare professionals to efficiently compare different enhancement techniques, streamlining the diagnostic workflow. The potential of this GUI lies in its ability to merge user-friendliness with powerful image processing capabilities, offering a comprehensive and efficient solution for medical professionals in clinical and research settings.

Item Type:	Article
Uncontrolled Keywords:	Image processing
Subjects:	T Technology > TA Engineering (General). Civil engineering (General) > TA1501-1820 Applied optics. Photonics
Divisions:	Faculty of Engineering and Technology (FET) Faculty of Information Science and Technology (FIST)
Depositing User:	Ms Rosnani Abd Wahab
Date Deposited:	30 Jun 2026 06:54
Last Modified:	30 Jun 2026 06:54
URII:	http://shdl.mmu.edu.my/id/eprint/16146

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