Proc IEEE Comput Soc Conf Comput Vis Pattern Recognit
June 2024
Introducing interpretability and reasoning into Multiple Instance Learning (MIL) methods for Whole Slide Image (WSI) analysis is challenging, given the complexity of gigapixel slides. Traditionally, MIL interpretability is limited to identifying salient regions deemed pertinent for downstream tasks, offering little insight to the end-user (pathologist) regarding the rationale behind these selections. To address this, we propose Self-Interpretable MIL (SI-MIL), a method intrinsically designed for interpretability from the very outset.
View Article and Find Full Text PDFProc IEEE Comput Soc Conf Comput Vis Pattern Recognit
June 2024
Conf Comput Vis Pattern Recognit Workshops
June 2024
Estimating uncertainty of a neural network is crucial in providing transparency and trustworthiness. In this paper, we focus on uncertainty estimation for digital pathology prediction models. To explore the large amount of unlabeled data in digital pathology, we propose to adopt novel learning method that can fully exploit unlabeled data.
View Article and Find Full Text PDFSatellite-based remote sensing and uncrewed aerial imagery play increasingly important roles in the mapping of wildlife populations and wildlife habitat, but the availability of imagery has been limited in remote areas. At the same time, ecotourism is a rapidly growing industry and can yield a vast catalog of photographs that could be harnessed for monitoring purposes, but the inherently ad-hoc and unstructured nature of these images make them difficult to use. To help address this, a subfield of computer vision known as phototourism has been developed to leverage a diverse collection of unstructured photographs to reconstruct a georeferenced three-dimensional scene capturing the environment at that location.
View Article and Find Full Text PDFSteatotic liver disease has been shown to associate with cardiovascular disease independently of other risk factors. Lipoproteins have been shown to mediate some of this relationship but there remains unexplained variance. Here we investigate the plasma lipidomic changes associated with liver steatosis and the mediating effect of these lipids on coronary artery disease (CAD).
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