2 citations · 3 across the 10 of their papers we have counts for
11 papers
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…
A Hierarchical Descriptor Framework for On-the-Fly Anatomical Location Matching between Longitudinal Studies
Halid Ziya Yerebakan, Yoshihisa Shinagawa, Mahesh Ranganath +2
We propose a method to match anatomical locations between pairs of medical images in longitudinal comparisons. The matching is made possible by computing a descriptor of the query…
Enhancing Health Data Interoperability with Large Language Models: A FHIR Study
Yikuan Li, Hanyin Wang, Halid Yerebakan +2
In this study, we investigated the ability of the large language model (LLM) to enhance healthcare data interoperability. We leveraged the LLM to convert clinical texts into their…
Deep Generative Neural Embeddings for High Dimensional Data Visualization
Halid Ziya Yerebakan, Gerardo Hermosillo Valadez
We propose a visualization technique that utilizes neural network embeddings and a generative network to reconstruct original data. This method allows for independent manipulation…
Supervised Understanding of Word Embeddings
Halid Ziya Yerebakan, Parmeet Bhatia, Yoshihisa Shinagawa
Pre-trained word embeddings are widely used for transfer learning in natural language processing. The embeddings are continuous and distributed representations of the words that pr…
Hierarchical Latent Word Clustering
Halid Ziya Yerebakan, Fitsum Reda, Yiqiang Zhan +1
This paper presents a new Bayesian non-parametric model by extending the usage of Hierarchical Dirichlet Allocation to extract tree structured word clusters from text data. The inf…