2 citations · 3 across the 10 of their papers we have counts for
6 papers · 1 filter
FD-AA: A Lightweight Focal-Diffuse And Attenuation-Aware Head for Incidental Abdominal Abnormality Detection in Chest CT
Haoyan Ding, Kritika Iyer, Halid Yerebakan +9
Routine chest CT captures upper-abdominal structures that may contain clinically relevant incidental abnormalities. Detecting these findings requires feature extraction from organs…
Fast Multi-Organ Fine Segmentation in CT Images with Hierarchical Sparse Sampling and Residual Transformer
Xueqi Guo, Halid Ziya Yerebakan, Yoshihisa Shinagawa +2
Multi-organ segmentation of 3D medical images is fundamental with meaningful applications in various clinical automation pipelines. Although deep learning has achieved superior per…
Consistent Point Matching
Halid Ziya Yerebakan, Gerardo Hermosillo Valadez
This study demonstrates that incorporating a consistency heuristic into the point-matching algorithm \cite{yerebakan2023hierarchical} improves robustness in matching anatomical loc…
BodyGPS: Anatomical Positioning System
Halid Ziya Yerebakan, Kritika Iyer, Xueqi Guo +2
We introduce a new type of foundational model for parsing human anatomy in medical images that works for different modalities. It supports supervised or unsupervised training and c…
Automatic Mapping of Anatomical Landmarks from Free-Text Using Large Language Models: Insights from Llama-2
Mohamad Abdi, Gerardo Hermosillo Valadez, Halid Ziya Yerebakan
Anatomical landmarks are vital in medical imaging for navigation and anomaly detection. Modern large language models (LLMs), like Llama-2, offer promise for automating the mapping…
Real Time Multi Organ Classification on Computed Tomography Images
Halid Ziya Yerebakan, Yoshihisa Shinagawa, Gerardo Hermosillo Valadez
Organ segmentation is a fundamental task in medical imaging since it is useful for many clinical automation pipelines. However, some tasks do not require full segmentation. Instead…