Mithun Kumar PK

Work place: Dept. of Computer Science & Engineering, Mawlana Bhashani Science and Technology University, Tangail-1902, Dhaka, Bangladesh



Research Interests: Pattern Recognition, Image Compression, Image Manipulation, Image Processing, Combinatorial Optimization


Mithun Kumar PK was born in Rajshahi, Bangladesh in 1989. He received the B.Sc Engineering degree in Computer Science & Engineering from Mawlana Bhashani Science and Technology University, Santosh, Tangail, Dhaka, Bangladesh, in 2012. He is currently working as a RESEARCHER with international research teams. He has approximately five years experience in digital image processing and medical image processing. His research interests include image analysis, image processing & medical image processing, pattern recognition, 3D visualization, Segmentation, Filter Optimization etc. Mr. PK’s has many international journal and conference publications all over the world. Now, he is a regular reviewer at IET Image Processing journal, Journal of Media and Communication studies, and International Arab Journal of Information Technology.

Author Articles
Automatically Gradient Threshold Estimation of Anisotropic Diffusion for Meyer’s Watershed Algorithm Based Optimal Segmentation

By Mithun Kumar PK Md. Gauhar Arefin Mohammad Motiur Rahman Abu Sayem Mohammad Delowar Hossain

DOI:, Pub. Date: 8 Nov. 2014

Medical image segmentation is a fundamental task in the medical imaging field. Optimal segmentation is required for the accurate judgment or appropriate clinical diagnosis. In this paper, we proposed automatically gradient threshold estimator of anisotropic diffusion for Meyer’s Watershed algorithm based optimal segmentation. The Meyer’s Watershed algorithm is the most significant for a large number of regions separations but the over segmentation is the major drawback of the Meyer’s Watershed algorithm. We are able to remove over segmentation after using anisotropic diffusion as a preprocessing step of segmentation in the Meyer’s Watershed algorithm. We used a fixed window size for dynamically gradient threshold estimation. The gradient threshold is the most important parameter of the anisotropic diffusion for image smoothing. The proposed method is able to segment medical image accurately because of obtaining the enhancement image. The introducing method demonstrates better performance without loss of any clinical information while preserving edges. Our investigated method is more efficient and effective in order to segment the region of interests in the medical images indeed.

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Metal Artifact Reduction from Computed Tomography (CT) Images using Directional Restoration Filter

By Mithun Kumar PK Mohammad Motiur Rahman

DOI:, Pub. Date: 8 May 2014

Computed tomography angiography (CTA) is a stabilized tool for vessel imaging in the medical image processing field. High-intense structures in the contrast image can seriously hamper luminal visualization. Metal artifacts are an extensive problem in computed tomography (CT) images. We proposed directional restoration filtering process with Fuzzy logic in order to reduce metal artifact from CT images. We create two sets by iteration process and these sets will be sorted in ascending order. After sorting we take two elements from two data sets and the tracking both elements will be selected from the second position of those sorting arrays. Intersection Fuzzy logic will be executed between two selected elements and Gaussian convolution operation will be performed in the entire images because of enhancement the artifact affected CT images. In this paper, we investigated a fully automated intensity-based filter and it depends on the gray level variation rating. This results in a better visualization of the vessel lumen, also of the smaller vessels, allowing a faster and more accurate inspection of the whole vascular structures.

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