390 citations · 2k across the 86 of their papers we have counts for
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METGAN: Generative Tumour Inpainting and Modality Synthesis in Light Sheet Microscopy
Izabela Horvath, Johannes C. Paetzold, Oliver Schoppe +6
Novel multimodal imaging methods are capable of generating extensive, super high resolution datasets for preclinical research. Yet, a massive lack of annotations prevents the broad…
Are we using appropriate segmentation metrics? Identifying correlates of human expert perception for CNN training beyond rolling the DICE coefficient
Florian Kofler, Ivan Ezhov, Fabian Isensee +16
Metrics optimized in complex machine learning tasks are often selected in an ad-hoc manner. It is unknown how they align with human expert perception. We explore the correlations b…
Imbalance-Aware Self-Supervised Learning for 3D Radiomic Representations
Hongwei Li, Fei-Fei Xue, Krishna Chaitanya +5
Radiomic representations can quantify properties of regions of interest in medical image data. Classically, they account for pre-defined statistics of shape, texture, and other low…
Deep Class-Specific Affinity-Guided Convolutional Network for Multimodal Unpaired Image Segmentation
Jingkun Chen, Wenqi Li, Hongwei Li +1
Multi-modal medical image segmentation plays an essential role in clinical diagnosis. It remains challenging as the input modalities are often not well-aligned spatially. Existing…