プロフィール詳細

プロジェクトを作成

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Dr. Subrata B.に依頼

Korea, South

Researcher | PhD in CSE | Smart Healthcare | Medical Image Analysis | Computer Vision | Computational Pathology | AI

プロフィール概要

I hold a B.Sc. in Information Technology from the University of Derby, UK (2016) and a Ph.D. in Computer Engineering from Inje University, Korea (2024). Currently, I am a Postdoctoral Researcher at the Medical Research Institute of Pusan National University, Korea, focusing on AI-driven solutions for healthcare. My work spans multimodal medical imaging, digital pathology, and smart healthcare, with specialization in: AI/computer vision for cancer diagnostics (prostate, breast, stomach, colorectal), Neurodegenerative diseases (Alzheimer’s and Parkinson) and Computational analysis of histopathology and MRI/CT images. I have numerous SCIE-indexed publications and hold related patents. I served as a reviewer for multiple academic journals (SCIE) and as an academic editor for the journal Prostate Cancer (Wiley). Additionally, I am currently serving as a Guest Editor for the Biomedicine Journal (MDPI). Key Skills & Expertise: 1. AI/Computer Vision: TensorFlow, PyTorch, and OpenCV for medical image analysis, segmentation, classification, detection, explainable AI. 2. Medical Imaging: Advanced analysis of histopathology (H&E, MRI), computer-aided diagnosis, including nuclei segmentation, tumor-stroma ratio quantification, and cancer detection. 3. Programming & Tools: Python, MATLAB, C++, R, and web development (HTML/CSS/JavaScript). Research Projects: Ongoing: 1. (June 2024 – Present): AI-integrated personal safe-infusion platform for untact auto-monitoring of drug administration accidents in hospital”. Supported by the National Research Foundation of Korea (NRF) Past: 1. (January 2019 – October 2020): Software development for tracking and quantitative analysis of hippocampal morphological changes according to the progression of Alzheimer's disease”. Supported by Basic Science Research Program through the National Research Foundation of Korea (NRF), funded by the Ministry of Education, Korea. 2. (October 2018 – December 2022): Intelligent Information Acceleration Open Ecosystem Development Project through collaboration with public institutions in Chungbuk”. Funded by Ministry of Trade, Industry, and Energy, (MOTIE), Korea, under the “Regional Specialized Industry Development Program” supervised by the Korea Institute for Advancement of Technology (KIAT) 3. (March 2022 – February 2024): Quantitative and Qualitative Analysis of Prostate Cancer Images: Development of Computer-aided Diagnosis Platform”. Supported by the National Research Foundation of Korea (NRF). 4. (March 2023 – December 2023): Development of Digital Pathology Platform Linked to Multi-Species Artificial Intelligence Solution”. Supported by the Korea Health Industry Development Institute (KHIDI).

専門分野

• ☆ Data Analysis
• ☆ Image Processing
• ☆ Artificial Intelligence
• ☆ Deep Learning
• ☆ Computer Vision
• ☆ Python
• ☆ Matlab
• ☆ R
• ☆ Cytopathology & Histopathology

サービス

• Writing
• Research
• Consulting
• Data & AI

Writing Technical Writing

Research Scientific and Technical Research, Systematic Literature Review

Consulting Healthcare Consulting, Scientific and Technical Consulting

Data & AI Image Processing, Image Analysis, Algorithm Design-Non ML, Algorithm Design-ML, Big Data Analytics, Text Mining & Analytics, Data Mining, Data Cleaning, Data Processing, Data Insights

職務経験

Postdoctoral Researcher

Pusan National University

6月 2024 - 現在

学歴

Doctor of Engineering (Computer Engineering)

Inje University

9月 2018 - 2月 2024

Bachelor (Information Technology)

University of Derby

10月 2013 - 6月 2016

認定資格

• Engineering Health: Introduction to Yoga and Physiology

  NYU Tandon School of Engineering (Coursera)

  https://www.coursera.org/account/accomplishments/verify/HGRGCHJ88OWP

  3月 2025 - 現在

• Rebuilding Our Relationship with Food

  Stanford University (Coursera)

  https://www.coursera.org/account/accomplishments/verify/6EFYEZNGIJTU

  2月 2025 - 現在

• Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization

  DeepLearning.AI (Coursera)

  https://www.coursera.org/account/accomplishments/verify/90VTQR3GOCEK

  1月 2025 - 現在

出版物

JOURNAL ARTICLE

Subrata Bhattacharjee, Jaewon Kim, Soo-Geun Wang, Jin-Choon Lee, Yong-Il Cheon, Sung-Chan Shin, Dong-Won Lim, Dae-Ik Jang, Yeong-Byn Hwang, Heung-Kook Choi, et al. (2024). Evaluation of Vertical Level Differences Between Left and Right Vocal Folds Using Artificial Intelligence System in Excised Canine Larynx . Journal of Voice.

Subrata Bhattacharjee, Rashadul Islam Sumon, Yeong-Byn Hwang, Hafizur Rahman, Hee-Cheol Kim, Wi-Sun Ryu, Dong Min Kim, Nam-Hoon Cho, Heung-Kook Choi (2023). Densely Convolutional Spatial Attention Network for nuclei segmentation of histological images for computational pathology . Frontiers in Oncology.

Subrata Bhattacharjee, Kobiljon Ikromjanov, Rashadul Islam Sumon, Yeong-Byn Hwang, Hafizur Rahman, Myung-Jae Lee, Hee-Cheol Kim, Eunhyang Park, Nam-Hoon Cho, Heung-Kook Choi (2023). Region Segmentation of Whole-Slide Images for Analyzing Histological Differentiation of Prostate Adenocarcinoma Using Ensemble EfficientNetB2 U-Net with Transfer Learning Mechanism . Cancers.

Kobiljon Ikromjanov, Subrata Bhattacharjee, PhD, Rashadul Islam Sumon, Yeong-Byn Hwang, Hafizur Rahman, Myung-Jae Lee, Hee-Cheol Kim, Eunhyang Park, 남훈 조, Heung Kook Choi (2023). Region Segmentation of Whole-Slide Images for Analyzing Histological Differentiation of Prostate Adenocarcinoma Using Ensemble EfficientNetB2 U-Net with Transfer Learning Mechanism . Cancers.

Subrata Bhattacharjee, Sikandar Ali, Ali Hussain, Ali Athar, Abdullah, Hee-Cheol Kim (2022). Detection of COVID-19 in X-ray Images Using Densely Connected Squeeze Convolutional Neural Network (DCSCNN): Focusing on Interpretability and Explainability of the Black Box Model . Sensors.

Sikandar Ali, Ali Hussain, Subrata Bhattacharjee, PhD, Ali Athar, Abdullah, Hee-Cheol Kim (2022). Detection of COVID-19 in X-ray Images Using Densely Connected Squeeze Convolutional Neural Network (DCSCNN): Focusing on Interpretability and Explainability of the Black Box Model . Sensors.

Subrata Bhattacharjee, Deekshitha Prakash, Cho-Hee Kim, Hee-Cheol Kim, Heung-Kook Choi(2022). Texture, Morphology, and Statistical Analysis to Differentiate Primary Brain Tumors on Two-Dimensional Magnetic Resonance Imaging Scans Using Artificial Intelligence Techniques . Healthcare Informatics Research. 28. (1). Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 46--57. The Korean Society of Medical Informatics

Subrata Bhattacharjee, Deekshitha Prakash, Nuwan Madusanka, Cho-Hee Kim, Hyeon-Gyun Park, Heung-Kook Choi (2021). Diagnosing Alzheimer’s Disease Based on Multiclass MRI Scans using Transfer Learning Techniques . Current Medical Imaging Formerly Current Medical Imaging Reviews.

Subrata Bhattacharjee, Kobiljon Ikromjanov, Kouayep Sonia Carole, Nuwan Madusanka, Nam-Hoon Cho, Yeong-Byn Hwang, Rashadul Islam Sumon, Hee-Cheol Kim, Heung-Kook Choi (2021). Cluster Analysis of Cell Nuclei in H&E-Stained Histological Sections of Prostate Cancer and Classification Based on Traditional and Modern Artificial Intelligence Techniques . Diagnostics.

Subrata Bhattacharjee, PhD, Kobiljon Ikromjanov, Kouayep Sonia Carole, Nuwan Madusanka Vithanage, Nam-Hoon Cho, Yeong-Byn Hwang, Rashadul Islam Sumon, Hee-Cheol Kim, Heung Kook Choi (2021). Cluster Analysis of Cell Nuclei in H&E-Stained Histological Sections of Prostate Cancer and Classification Based on Traditional and Modern Artificial Intelligence Techniques . Diagnostics.

Subrata Bhattacharjee, Hye‐Kyung Lee, Cho‐Hee Kim, Hyeon‐Gyun Park, Deekshitha Prakash, Heung‐Kook Choi (2021). A Paradigm Shift in Nuclear Chromatin Interpretation: From Qualitative Intuitive Recognition to Quantitative Texture Analysis of Breast Cancer Cell Nuclei . Cytometry Part A.

Subrata Bhattacharjee, Cho-Hee Kim, Deekshitha Prakash, Suki Kang, Nam-Hoon Cho, Hee-Cheol Kim, Heung-Kook Choi(2021). Artificial Intelligence Techniques for Prostate Cancer Detection through Dual-Channel Tissue Feature Engineering . Cancers. 13. (7). Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 1524. {MDPI} {AG}

Cho-Hee Kim, Subrata Bhattacharjee, PhD, Deekshitha Prakash, Suki Kang, Nam-Hoon Cho, Hee-Cheol Kim, Heung Kook Choi (2021). Artificial Intelligence Techniques for Prostate Cancer Detection through Dual-Channel Tissue Feature Engineering . Cancers.

Multichannel Convolution Neural Network Classification for the Detection of Histological Pattern in Prostate Biopsy Images @article{10.9717/KMMS.2020.23.12.1486, author = {BhattacharjeeSubrata and PrakashDeekshitha and KimCho-Hee and ChoiHeung-Kook}, title = {}, journal = {한국멀티미디어학회논문지}, publisher = {한국멀티미디어학회}, volume = {23}, number = {12}, pages = {1486-1495} year = 2020, month = 12} . 한국멀티미디어학회논문지.

Subrata Bhattacharjee, Cho-Hee Kim, Deekshitha Prakash, Hyeon-Gyun Park, Nam-Hoon Cho, Heung-Kook Choi(2020). An Efficient Lightweight CNN and Ensemble Machine Learning Classification of Prostate Tissue Using Multilevel Feature Analysis . Applied Sciences. 10. (22). Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 8013. {MDPI} {AG}

Subrata Bhattacharjee, PhD, Cho-Hee Kim, Deekshitha Prakash, Hyeon-Gyun Park, Nam-Hoon Cho, Heung Kook Choi (2020). An Efficient Lightweight CNN and Ensemble Machine Learning Classification of Prostate Tissue Using Multilevel Feature Analysis . Applied Sciences.

(2020). 다양한 이미지 향상 기법을 사용한 전립선 병리영상 딥러닝 이진 분류 연구 . 한국멀티미디어학회논문지.

Subrata Bhattacharjee, Boo-Kyeong Choi, Nuwan Madusanka, Heung-Kook Choi, Jae-Hong So, Cho-Hee Kim, Hyeon-Gyun Park, Deekshitha Prakash(2020). Convolutional Neural Network-based MR Image Analysis for Alzheimer’s Disease Classification . Current Medical Imaging Formerly Current Medical Imaging Reviews. 16. (1). Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 27--35. Bentham Science Publishers Ltd.

Choi, B.-K., Madusanka, N., Choi, H.-K., So, J.-H., Kim, C.-H., Park, H.-G., Bhattacharjee, S., Prakash, D.(2020). Convolutional neural network-based mr image analysis for Alzheimer’s disease classification . Current Medical Imaging. 16. (1). Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 27-35.

(2019). A Comparative Study of Alzheimer’s Disease Classification using Multiple Transfer Learning Models . Journal of Multimedia Information System.

Subrata Bhattacharjee, Cho-Hee Kim, Hyeon-Gyun Park, Deekshitha Prakash, Nuwan Madusanka, Nam-Hoon Cho, Heung-Kook Choi(2019). Multi-Features Classification of Prostate Carcinoma Observed in Histological Sections: Analysis of Wavelet-Based Texture and Colour Features . Cancers. 11. (12). Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 1937. {MDPI} {AG}

Subrata Bhattacharjee, PhD, Cho-Hee Kim, Hyeon-Gyun Park, Deekshitha Prakash, Nuwan Madusanka Vithanage, Nam-Hoon Cho, Heung Kook Choi (2019). Multi-Features Classification of Prostate Carcinoma Observed in Histological Sections: Analysis of Wavelet-Based Texture and Colour Features . Cancers.

(2019). 전립선암의 정확한 진단을 위한 질감 특성 분석 및 등급 분류 . 한국멀티미디어학회논문지.

Subrata Bhattacharjee, Hyeon-Gyun Park, Cho-Hee Kim, Deekshitha Prakash, Nuwan Madusanka, Jae-Hong So, Nam-Hoon Cho, Heung-Kook Choi (2019). Quantitative Analysis of Benign and Malignant Tumors in Histopathology: Predicting Prostate Cancer Grading Using SVM . Applied Sciences.

Subrata Bhattacharjee, PhD, Hyeon-Gyun Park, Cho-Hee Kim, Deekshitha Prakash, Nuwan Madusanka, Jae-Hong So, Nam-Hoon Cho, Heung Kook Choi (2019). Quantitative Analysis of Benign and Malignant Tumors in Histopathology: Predicting Prostate Cancer Grading Using SVM . Applied Sciences.

Bhattacharjee, S., Kim, C.-H., Park, H.-G., Prakash, D., Madusanka, N., Cho, N.-H., Choi, H.-K.(2019). Multi-features classification of prostate carcinoma observed in histological sections: Analysis of wavelet-based texture and colour features . Cancers. 11. (12).

Bhattacharjee, S., Park, H.-G., Kim, C.-H., Prakash, D., Madusanka, N., So, J.-H., Cho, N.-H., Choi, H.-K.(2019). Quantitative analysis of benign and malignant tumors in histopathology: Predicting prostate cancer grading using SVM . Applied Sciences (Switzerland). 9. (15).

PATENT

(2022). A method for Prostate Cancer Grade Classification Using Support Vector Machine (서포트 벡터 머신을 이용한 전립선암의 등급 분류 방법).

(2022). A method for multi-attribute classification of prostate cancer types in histological sections (조직학 섹션에서 전립선암 종의 다중 특성 분류 방법).

CONFERENCE PAPER

Subrata Bhattacharjee and Yeong-Byn Hwang and Kobiljon Ikromjanov and Rashadul Islam Sumon and Hee-Cheol Kim and Heung-Kook Choi(2022). An Explainable Computer Vision in Histopathology: Techniques for Interpreting Black Box Model . 2022 International Conference on Artificial Intelligence in Information and Communication (ICAIIC). {IEEE}

Kobiljon Ikromjanov and Subrata Bhattacharjee and Yeong-Byn Hwang and Rashadul Islam Sumon and Hee-Cheol Kim and Heung-Kook Choi(2022). Whole Slide Image Analysis and Detection of Prostate Cancer using Vision Transformers . 2022 International Conference on Artificial Intelligence in Information and Communication (ICAIIC). {IEEE}

Subrata Bhattacharjee and Kobiljon Ikromjanov and Yeong-Byn Hwang and Rashadul Islam Sumon and Hee-Cheol Kim and Heung-Kook Choi(2021). Detection and Classification of Prostate Cancer Using Dual-Channel Parallel Convolution Neural Network . Proceedings of the Future Technologies Conference (FTC) 2021. Microsoft.AspNetCore.Mvc.Localization.LocalizedHtmlString 66--83. Springer International Publishing