25 papers
Learning from Complementary Ultrasound Representations for Liver Disease Classification
Sabahattin Mert Daloglu, Gokce Bekar, Ceren Coskun +5
The paper studies whether adding physics-guided and local phase ultrasound representations to conventional B-mode images improves classification of NASH versus NAFLD, using self-su…
Analyzing Image Encoder Choices and Graph Homophily in GCN Frameworks for Breast Ultrasound Classification
Sabahattin Mert Daloglu, Ceren Coskun, Harvey Castro +2
The paper evaluates how different image encoders, including CNNs and vision transformers, affect graph construction and classification performance in graph convolutional network mo…
VAMPS: Visual-Assisted Mathematical Problem Solving Benchmark
Amirhossein Dabiriaghdam, Shayan Vassef, Mohammadreza Bakhtiari +5
Multimodal large language models are increasingly capable of complex reasoning, yet their performance often degrades when they must externalize a problem through a tool and then re…
XTinyU-Net: Training-Free U-Net Scaling via Initialization-Time Sensitivity
Alvin Kimbowa, Moein Heidari, David Liu +1
While U-Net architectures remain the gold standard for medical image segmentation, their deployment in resource-constrained environments demands aggressive model compression. Howev…
MonoUNet: A Robust Tiny Neural Network for Automated Knee Cartilage Segmentation on Point-of-Care Ultrasound Devices
Alvin Kimbowa, Arjun Parmar, Ibrahim Mujtaba +5
Objective: To develop a robust and compact deep learning model for automated knee cartilage segmentation on point-of-care ultrasound (POCUS) devices. Methods: We propose MonoUNet,…
A Clinically Anchored Radiomics Dictionary for Explainable TI-RADS-Based Thyroid Nodule Classification in Ultrasound; Dictionary Version TU1.0
Mohammad Salmanpour, Shahram Taeb, Ali Fathi Jouzdani +5
Artificial intelligence based radiomics models for thyroid ultrasound (US) often achieve strong diagnostic performance but remain difficult to interpret, limiting clinical trust an…