1.1k citations · 4.6k across the 64 of their papers we have counts for
68 papers
Correcting Class Imbalances with Self-Training for Improved Universal Lesion Detection and Tagging
Alexander Shieh, Tejas Sudharshan Mathai, Jianfei Liu +2
Universal lesion detection and tagging (ULDT) in CT studies is critical for tumor burden assessment and tracking the progression of lesion status (growth/shrinkage) over time. Howe…
3D Universal Lesion Detection and Tagging in CT with Self-Training
Jared Frazier, Tejas Sudharshan Mathai, Jianfei Liu +2
Radiologists routinely perform the tedious task of lesion localization, classification, and size measurement in computed tomography (CT) studies. Universal lesion detection and tag…
Universal Lesion Detection in CT Scans using Neural Network Ensembles
Tarun Mattikalli, Tejas Sudharshan Mathai, Ronald M. Summers
In clinical practice, radiologists are reliant on the lesion size when distinguishing metastatic from non-metastatic lesions. A prerequisite for lesion sizing is their detection, a…
Lymph Node Detection in T2 MRI with Transformers
Tejas Sudharshan Mathai, Sungwon Lee, Daniel C. Elton +4
Identification of lymph nodes (LN) in T2 Magnetic Resonance Imaging (MRI) is an important step performed by radiologists during the assessment of lymphoproliferative diseases. The…
A Graph-theoretic Algorithm for Small Bowel Path Tracking in CT Scans
Seung Yeon Shin, Sungwon Lee, Ronald M. Summers
We present a novel graph-theoretic method for small bowel path tracking. It is formulated as finding the minimum cost path between given start and end nodes on a graph that is cons…
RATCHET: Medical Transformer for Chest X-ray Diagnosis and Reporting
Benjamin Hou, Georgios Kaissis, Ronald Summers +1
Chest radiographs are one of the most common diagnostic modalities in clinical routine. It can be done cheaply, requires minimal equipment, and the image can be diagnosed by every…