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6 papers · 2 filters
Blind deblurring for microscopic pathology images using deep learning networks
Cheng Jiang, Jun Liao, Pei Dong +6
Artificial Intelligence (AI)-powered pathology is a revolutionary step in the world of digital pathology and shows great promise to increase both diagnosis accuracy and efficiency.…
Brain Atlas Guided Attention U-Net for White Matter Hyperintensity Segmentation
Zicong Zhang, Kimerly Powell, Changchang Yin +4
White Matter Hyperintensities (WMH) are the most common manifestation of cerebral small vessel disease (cSVD) on the brain MRI. Accurate WMH segmentation algorithms are important t…
Self-Loop Uncertainty: A Novel Pseudo-Label for Semi-Supervised Medical Image Segmentation
Yuexiang Li, Jiawei Chen, Xinpeng Xie +2
Witnessing the success of deep learning neural networks in natural image processing, an increasing number of studies have been proposed to develop deep-learning-based frameworks fo…
Multi-Task Neural Networks with Spatial Activation for Retinal Vessel Segmentation and Artery/Vein Classification
Wenao Ma, Shuang Yu, Kai Ma +3
Retinal artery/vein (A/V) classification plays a critical role in the clinical biomarker study of how various systemic and cardiovascular diseases affect the retinal vessels. Conve…
Revisiting Rubik's Cube: Self-supervised Learning with Volume-wise Transformation for 3D Medical Image Segmentation
Xing Tao, Yuexiang Li, Wenhui Zhou +2
Deep learning highly relies on the quantity of annotated data. However, the annotations for 3D volumetric medical data require experienced physicians to spend hours or even days fo…
Generalized Octave Convolutions for Learned Multi-Frequency Image Compression
Mohammad Akbari, Jie Liang, Jingning Han +1
Learned image compression has recently shown the potential to outperform the standard codecs. State-of-the-art rate-distortion (R-D) performance has been achieved by context-adapti…