Titlebook: Medical Image Understanding and Analysis; 23rd Conference, MIU Yalin Zheng,Bryan M. Williams,Ke Chen Conference proceedings 2020 Springer N

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Spatial Modelling of Retinal Thickness in Images from Patients with Diabetic Macular Oedemae data being spatially collected, current approaches are not spatial: they involve analysing each location separately, or they analyse all image sectors together but they ignore the possible spatial correlations such as linear models, and multivariate analysis of variance (MANOVA). We propose spatia

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Incremental Learning of Fetal Heart Anatomies Using Interpretable Saliency Mapse to tendencies of degradation in performance over old tasks while adapting to novel tasks. It is pertinent that adaptations to new data distributions over time are tractable with automated analysis methods as medical imaging data acquisition is typically not a static problem. So, one needs to ensur

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Multi-task CNN for Structural Semantic Segmentation in 3D Fetal Brain Ultrasounduse of convolutional neural networks (CNNs) for the segmentation of multiple fetal brain structures in 3D ultrasound images. Accurate automatic segmentation of brain structures in fetal ultrasound images can track brain development through gestation, and can provide useful information that can help

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Conference proceedings 2020in July 2019...The 43 full papers presented were carefully reviewed and selected from 70 submissions. There were organized in topical sections named: oncology and tumour imaging; lesion, wound and ulcer analysis; biostatistics; fetal imaging; enhancement and reconstruction; diagnosis, classification

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