21 citations · 35 across the 7 of their papers we have counts for
8 papers
Integrating Local Detail and Global Context: A Dual-Input Multi-Task Learning Framework for Bone Tumor Diagnosis
S. M. Nasif Uddin, Rusab Sarmun, Muhammad E. H. Chowdhury +3
Primary bone tumors are rare but clinically aggressive neoplasms whose diagnosis from radiographs is challenged by heterogeneous morphology, subtle lesion margins, and overlapping…
ResNet-34 with Lightweight Decoder for Accurate and Efficient Segmentation of Fetal Brain MRI
Ashiqur Rahman, Muhammad E. H. Chowdhury, Md. Abu Sayed +3
Accurate segmentation of fetal brain tissues in Magnetic Resonance Imaging (MRI) is critical for early diagnosis of congenital abnormalities and improving prenatal care. However, t…
A Two-Stage Deep Learning Framework for Segmentation of Ten Gastrointestinal Organs from Coronal MR Enterography
Ashiqur Rahman, Md. Abu Sayed, Md Sharjis Ibne Wadud +3
Accurate segmentation of gastrointestinal (GI) organs in magnetic resonance enterography (MRE) is critical for diagnosing inflammatory bowel disease (IBD). However, anatomical vari…
Tracing 3D Anatomy in 2D Strokes: A Multi-Stage Projection Driven Approach to Cervical Spine Fracture Identification
Fabi Nahian Madhurja, Rusab Sarmun, Muhammad E. H. Chowdhury +3
Cervical spine fractures require rapid and accurate diagnosis, yet automatic CT interpretation remains challenging as subtle injuries must be assessed across large 3D volumes. We a…
Deep Learning-Driven Segmentation of Ischemic Stroke Lesions Using Multi-Channel MRI
Ashiqur Rahman, Muhammad E. H. Chowdhury, Md Sharjis Ibne Wadud +4
Ischemic stroke, caused by cerebral vessel occlusion, presents substantial challenges in medical imaging due to the variability and subtlety of stroke lesions. Magnetic Resonance I…
Machine-agnostic Automated Lumbar MRI Segmentation using a Cascaded Model Based on Generative Neurons
Promit Basak, Rusab Sarmun, Saidul Kabir +5
Automated lumbar spine segmentation is very crucial for modern diagnosis systems. In this study, we introduce a novel machine-agnostic approach for segmenting lumbar vertebrae and…
Self-DenseMobileNet: A Robust Framework for Lung Nodule Classification using Self-ONN and Stacking-based Meta-Classifier
Md. Sohanur Rahman, Muhammad E. H. Chowdhury, Hasib Ryan Rahman +4
In this study, we propose a novel and robust framework, Self-DenseMobileNet, designed to enhance the classification of nodules and non-nodules in chest radiographs (CXRs). Our appr…
Deep learning in computed tomography pulmonary angiography imaging: a dual-pronged approach for pulmonary embolism detection
Fabiha Bushra, Muhammad E. H. Chowdhury, Rusab Sarmun +7
The increasing reliance on Computed Tomography Pulmonary Angiography (CTPA) for Pulmonary Embolism (PE) diagnosis presents challenges and a pressing need for improved diagnostic so…