Portrait of Halima Khatun

Halima Khatun

  • Research Assistant, CCDS

Bachelors, Independent University, Bangladesh

Publications (8)

Siam Tahsin Bhuiyan, Rashedur Rahman, Sefatul Wasi, Halima Khatun, Ashraful Islam, AKM Mahbubur Rahman, Saadia Binte Alam, M Ashraful Amin

PelviNeXt: A Modality-Agnostic Hybrid Network for Pelvic Imaging in Women's Health

arXiv (Cornell University), 2026

Preprint / Working PaperDOIURL
  • perceptual hashing
  • pelvic radiography
  • multi-scale feature fusion
  • polycystic ovary syndrome
  • channel and spatial attention
  • pelvic fractures
  • pelvic ultrasound
  • multi-head self-attention
  • SDG 3Good Health and Well-being
  • SDG 5Gender Equality

Sadia Alam Kotha, Abdullah Al Alam Shanto, Mumtahina Esha, Siam Tahsin Bhuiyan, Halima Khatun, Rashedur Rahman, Ashraful Islam, Saadia Binte Alam

Learning From Both Eyes: A Bilateral Ensemble Approach for Retinal Disease Classification

2025 IEEE International Women in Engineering (WIE) Conference on Electrical and Computer Engineering (WIECON-ECE), pp. 480-485, 2025

Conference PaperDOIURL
  • age-related macular degeneration
  • myopia
  • retinal disease classification
  • cataract
  • diabetic retinopathy
  • color fundus images
  • color correction
  • SDG 3Good Health and Well-being

Siam Tahsin Bhuiyan, Halima Khatun, Samiul Karim Mazumder, Fatin Israq, Riyadul Islam, Rashedur Rahman, Ashraful Islam, Saadia Binte Alam

The Role of Model Architecture in Breast Cancer Classification: A Comparison of CNN and Transformer Paradigms on Ultrasound Data

2025 IEEE International Women in Engineering (WIE) Conference on Electrical and Computer Engineering (WIECON-ECE), pp. 356-361, 2025

Conference PaperDOIURL
  • DenseNet121
  • breast cancer classification
  • Swin Transformer
  • model architecture comparison
  • breast ultrasound
  • BUSI dataset
  • ConvNeXt
  • CNN-Transformer hybrid
  • vision transformer
  • self-attention
  • SDG 3Good Health and Well-being

Md Zafor Iqbal, Siam Tahsin Bhuiyan, Riyadul Islam, Halima Khatun, Samiul Karim Mazumder, Rashedur Rahman, Ashraful Islam, Saadia Binte Alam

A Two-Stage Deep Learning Framework for Liver and Hepatocellular Carcinoma Segmentation on MRI

2025 IEEE International Conference on Biomedical Engineering, Computer and Information Technology for Health (BECITHCON), pp. 359-364, 2025

Conference PaperDOIURL
  • U-Net
  • Hepatocellular carcinoma
  • tumor segmentation
  • liver segmentation
  • Magnetic resonance imaging
  • two-stage segmentation
  • train-test split
  • data bias
  • Dice coefficient
  • small cohorts
  • SDG 3Good Health and Well-being