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Results for "class activation": 4 found

A Novel Margin-Based Focal Distance Loss for Lesion Segmentation in Medical Imaging

Authors: Weiguo Lu, Hua-Chieh Shao, Guoping Xu, You Zhang

Affiliation: Medical Artificial Intelligence and Automation (MAIA) Lab, Department of Radiation Oncology, UT Southwestern Medical Center, Medical Artificial Intelligence and Automation (MAIA) Laboratory, Department of Radiation Oncology, UT Southwestern Medical Center

Abstract Preview: Purpose:
Neural network-based lesion segmentation remains a significant challenge due to the low contrast between lesions and surrounding tissues (high ambiguity) and the variability of lesion shap...

Cerebellar Mutism Syndrome Prediction with 3D Residual Convolutional Neural Network

Authors: Sahaja Acharya, Matthew Ladra, Junghoon Lee, Lina Mekki, Bohua Wan

Affiliation: Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Department of Biomedical Engineering, Johns Hopkins University, Department of Computer Science, Johns Hopkins University

Abstract Preview: Purpose: Cerebellar mutism syndrome (CMS) is the most frequently observed complication in children undergoing surgical resection of posterior fossa tumors. Previous work explored lesion to symptom map...

Explainable Xerostomia Prediction with Decoupled High Resolution Class Activation Map

Authors: Junghoon Lee, Todd R. McNutt, Harry Quon, Bohua Wan

Affiliation: Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Johns Hopkins University, Department of Computer Science, Johns Hopkins University

Abstract Preview: Purpose: Xerostomia is a common toxicity in head and neck cancer (HNC) radiotherapy (RT). A few deep learning (DL) models have been proposed to predict the chance of xerostomia 12 months after RT with...

Improving Mammography Diagnosis Accuracy through Global Context and Local Lesion Integration

Authors: Minbin Chen, Xiaoyi Dai, Xiaoyu Duan, Chunhao Wang, Fan Xia, Zhenyu Yang, Fang-Fang Yin, Chulong Zhang, Rihui Zhang

Affiliation: Duke University, Duke Kunshan University, Medical Physics Graduate Program, Duke Kunshan University, The First People's Hospital of Kunshan

Abstract Preview: Purpose: Deep learning (DL)-based mammography diagnosis presents unique challenges, as accurate interpretation requires both global breast condition analysis and local lesion structural information. E...