Hossain Lab
AI for Medical Imaging (AIM)
AIM Lab (Artificial Intelligence for Medical Imaging) is committed to advancing artificial intelligence technologies in medical imaging, with a particular emphasis on digital and computational pathology. Led by Dr. Hossain Md Shakhawat, Associate Professor at Kochi University of Technology (KUT), the lab focuses on developing AI-powered solutions for medical image analysis to improve diagnostic accuracy and support clinical decision-making. The lab’s core research areas include cancer detection, grading, and staging and applying computer vision techniques in pathology. Through innovative and interdisciplinary research, AIM Lab strives to drive breakthroughs in AI-enabled diagnostics and foster the integration of data-driven approaches in modern healthcare.
Research Projects
Advancing the field of AI and medical imaging
Multimodal AI for Breast Cancer Subtype Analysis and Precision Therapy Recommendation
This project aims to develop a multimodal AI system that analyzes diverse breast cancer data—including histopathology, clinical, genetic, and imaging data—to accurately determine cancer …
Automated Diganosis Pipeline for Breast Cancer Metastasis Assessment
This research aims to develop an AI-guided automated pipeline for assessing breast cancer metastases in distant and axillary lymph nodes using affordable digital images of H&E-stained biopsy specimens. Traditional imaging methods (e.g., …
HER2 Grading of Breast Cancer Patients
Our lab handles large-scale data to extract meaningful insights through statistical modeling, predictive analysis, and data visualization. We aim to support data-driven decision making.
Residual Tumor Cellularity Assessment After Neoadjuvant Therapy
Residual Tumor Cellularity (RTC) assessment after neoadjuvant therapy is essential for evaluating treatment response and guiding further clinical decisions in breast cancer care. We intend …
AI-guided Solution for Selecting Ovarian Cancer Patients for Bevacizumab Monoclonal Therapy
Ovarian cancer treatment outcomes can vary significantly among patients, making personalized therapy selection crucial. This research aims to develop an AI-guided solution leveraging advanced multimodal …
Nuclei Segmentation in Histopathology Images
This research project focuses on developing advanced AI algorithms for accurate nuclei segmentation in histopathology images, a critical step in computational pathology. Precise segmentation …
Join Our Research Community
We're always looking for talented researchers to collaborate with us and advance the field of AI in medical imaging