5 papers
3D Ultrasound-Derived Pseudo-CT Synthesis Using a Transformer-Augmented Residual Network for Real-Time Operator Guidance
Sapna Sachan, Amulya Kumar Mahto
Computed tomography (CT) is indispensable for clinical diagnosis and image-guided interventions but exposes patients to ionizing radiation, motivating the development of safer imag…
A Robust Unsupervised Domain Adaptation Framework for Medical Image Classification Using RKHS-MMD
Sapna Sachan, Rakesh Kumar Sanodiya, Amulya Kumar Mahto
Labeling medical images is a major bottleneck in the field of medical imaging, as it requires domain-specific expertise, and it gets further complicated due to variability across d…
Orientation-Aware Unsupervised Domain Adaptation for Brain Tumor Classification Across Multi-Modal MRI
Sapna Sachan, Amulya Kumar Mahto, Prashant Wagambar Patil
The clinical integration of deep learning models for brain tumor diagnosis in neuro-oncology is severely constrained by limited expert-annotated MRI data and substantial inter-inst…
MK-ResRecon: Multi-Kernel Residual Framework for Texture-Aware 3D MRI Refinement from Sparse 2D Slices
Prajyot Pyati, Sapna Sachan, Amulya Kumar Mahto +1
Magnetic Resonance Imaging (MRI) acquisition remains a time-intensive and patient-straining process, as prolonged scan dura- tions increase the likelihood of motion artifacts, whic…
Skin Cancer Classification: Hybrid CNN-Transformer Models with KAN-Based Fusion
Shubhi Agarwal, Amulya Kumar Mahto
Skin cancer classification is a crucial task in medical image analysis, where precise differentiation between malignant and non-malignant lesions is essential for early diagnosis a…