Bootstrapping Semi-supervised Medical Image Segmentation with Anatomical-Aware Contrastive Distillation
Inf Process Med Imaging. 2023 Jun;13939:641-653. doi: 10.1007/978-3-031-34048-2_49. Epub 2023 Jun 8.ABSTRACTContrastive learning has shown great promise over annotation scarcity problems in the context of medical image segmentation. Existing approaches typically assume a balanced class distribution for both labeled and unlabeled medical images. However, medical image data in reality is commonly imbalanced (i.e., multi-class label imbalance), which naturally yields blurry contours and usually incorrectly labels rare objects. Moreover, it remains unclear whether all negative samples are equally negative. In this work, we pre...
Source: Inf Process Med Imaging - July 6, 2023 Category: Radiology Authors: Chenyu You Weicheng Dai Yifei Min Lawrence Staib James S Duncan Source Type: research
Bayesian Longitudinal Modeling of Early Stage Parkinson's Disease Using DaTscan Images
Inf Process Med Imaging. 2019 Jun;11492:405-416. doi: 10.1007/978-3-030-20351-1_31. Epub 2019 May 22.ABSTRACTThis paper proposes a disease progression model for early stage Parkinson's Disease (PD) based on DaTscan images. The model has two novel aspects: first, the model is fully coupled across the two caudates and putamina. Second, the model uses a new constraint called model mirror symmetry (MMS). A full Bayesian analysis, with collapsed Gibbs sampling using conjugate priors, is used to obtain posterior samples of the model parameters. The model identifies PD progression subtypes and reveals novel fast modes of PD progr...
Source: Inf Process Med Imaging - June 13, 2023 Category: Radiology Authors: Yuan Zhou Hemant D Tagare Source Type: research
