Developing a Machine Learning-Based Clinical Decision Support Tool for Uterine Tumor Imaging

no code implementations • 20 Aug 2023 • Darryl E. Wright, Adriana V. Gregory, Deema Anaam, Sepideh Yadollahi, Sumana Ramanathan, Kafayat A. Oyemade, Reem Alsibai, Heather Holmes, Harrison Gottlich, Cherie-Akilah G. Browne, Sarah L. Cohen Rassier, Isabel Green, Elizabeth A. Stewart, Hiroaki Takahashi, Bohyun Kim, Shannon Laughlin-Tommaso, Timothy L. Kline

On imaging, it is difficult to differentiate LMS from, for example, degenerated leiomyoma (LM), a prevalent but benign condition.

feature selection

Role of Image Acquisition and Patient Phenotype Variations in Automatic Segmentation Model Generalization

no code implementations • 26 Jul 2023 • Timothy L. Kline, Sumana Ramanathan, Harrison C. Gottlich, Panagiotis Korfiatis, Adriana V. Gregory

Purpose: This study evaluated the out-of-domain performance and generalization capabilities of automated medical image segmentation models, with a particular focus on adaptation to new image acquisitions and disease type.

Image Segmentation Medical Image Segmentation +1

Realistic Ultrasound Image Synthesis for Improved Classification of Liver Disease

no code implementations • 27 Jul 2021 • Hui Che, Sumana Ramanathan, David Foran, John L Nosher, Vishal M Patel, Ilker Hacihaliloglu

With the success of deep learning-based methods applied in medical image analysis, convolutional neural networks (CNNs) have been investigated for classifying liver disease from ultrasound (US) data.

Classification Generative Adversarial Network +1