8 papers · 1 filter
LoGSAM: Parameter-Efficient Cross-Modal Grounding for MRI Segmentation
Mohammad Robaitul Islam Bhuiyan, Sheethal Bhat, Melika Qahqaie +4
Precise localization and delineation of brain tumors using magnetic resonance imaging (MRI) are essential for planning therapy and guiding surgical decisions. To address this, we p…
Pseudo-Text-Conditioned 3D Grounding DINO for Organ Localization in Abdominal CT
Siqi Chen, Han Gong, Keyi Hou +3
Reliable organ localization in abdominal CT can provide spatial priors for downstream trauma analysis. We propose CT-3GDINO, a lightweight 3D detector that adapts a Grounding-DINO-…
CT-VDETR: Semi-supervised 3D Trauma Detection in Computed Tomography (CT) scans using Dense Vertex Relative Position Encoding
Shivam Chaudhary, Sheethal Bhat, Andreas Maier
Accurate detection and localization of traumatic injuries in abdominal CT remain challenging because voxel-level annotations are limited and expensive to obtain. We present a label…
Retina-RAG: Retrieval-Augmented Vision-Language Modeling for Joint Retinal Diagnosis and Clinical Report Generation
Abdelrahman Zaian, Sheethal Bhat, Mohamed Abdalkader +1
Diabetic Retinopathy (DR) is a leading cause of preventable blindness among working-age adults worldwide, yet most automated screening systems are limited to image-level classifica…
Benchmarking CNN-based Models against Transformer-based Models for Abdominal Multi-Organ Segmentation on the RATIC Dataset
Lukas Bayer, Sheethal Bhat, Andreas Maier
Accurate multi-organ segmentation in abdominal CT scans is essential for computer-aided diagnosis and treatment. While convolutional neural networks (CNNs) have long been the stand…
Exemplar Med-DETR: Toward Generalized and Robust Lesion Detection in Mammogram Images and beyond
Sheethal Bhat, Bogdan Georgescu, Adarsh Bhandary Panambur +8
Detecting abnormalities in medical images poses unique challenges due to differences in feature representations and the intricate relationship between anatomical structures and abn…