Dibash Basukala

Dibash Basukala
NYU Langone Health · Department of Radiology

PhD in Computer Science

About

7
Publications
621
Reads
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24
Citations
Additional affiliations
October 2017 - March 2021
University of Canterbury
Position
  • PhD Researcher
Description
  • MRI Image Segmentation, Image Feature Extraction, Medical Image Analysis, Data Analysis, Machine Learning, Brain Imaging and its application to Parkinson's Disease
September 2014 - February 2017
Chosun University
Position
  • Research Assistant
Description
  • Image Processing, MRI Image Segmentation, Medical Image Analysis
Education
October 2017 - March 2021
University of Canterbury
Field of study
  • Computer Science
September 2014 - August 2016
Chosun University
Field of study
  • Information and Communication Engineering

Publications

Publications (7)
Article
Accurate segmentation of substantia nigra (SN) and red nucleus (RN) is challenging, yet important for understanding health problems like Parkinson's disease (PD). This paper proposes an algorithm to segment SN and RN from quantitative susceptibility mapping (QSM) MRI and use the results to investigate PD. Algorithm-derived segments (based on level...
Article
Full-text available
Image segmentation is an important step in most medical image analysis tasks. An effective image segmentation method helps clinicians and patients in image-guided surgery, radiotherapy, early disease detection, volumetric measurement, and three-dimensional visualization. The fuzzy c-means (FCM) clustering algorithm is one of the most popular method...
Article
Full-text available
Watershed transformation is an effective segmentation algorithm that originates from the mathematical morphology field. This algorithm is widely used in medical image segmentation because it produces complete division even under poor contrast. However, over-segmentation is its most significant limitation. Therefore, this article proposes a combinat...
Article
Watershed Transformation is a popular segmentation method coming from the field of mathematical morphology. Different kernels such as rice, wheat, and corn are over-segmented by the traditional watershed algorithm. Therefore, this paper proposes an improved watershed segmentation algorithm by automatic selection of threshold value using moment pres...

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