Titlebook: Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support; 4th International Wo Danail Stoyanov,Zeike T

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https://doi.org/10.1007/978-3-642-24034-8 into account any prior knowledge about the shape of the biomedical structures being segmented. More recently, some works have presented approaches to incorporate shape information. However, many of them are indeed introducing more parameters to the segmentation network to learn the general features

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Molecular Methods to Detect , and , in Foods. We introduce a novel particle tracking approach using an LSTM-based neural network. Our approach determines assignment probabilities jointly across multiple detections by exploiting both short and long-term temporal dependencies of individual object dynamics. Manually labeled data is not required.

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https://doi.org/10.1007/978-90-481-8544-3autism, Alzheimer’s disease, and stroke. While a growing number of studies have demonstrated the promise of machine learning algorithms for rs-fMRI based clinical or behavioral prediction, most prior models have been limited in their capacity to exploit the richness of the data. For example, classif