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Cascaded Fully Convolutional Networks for automatic prenatal ultrasound image segmentation.

, , , , , and . ISBI, page 663-666. IEEE, (2017)

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Bootstrap Representation Learning for Segmentation on Medical Volumes and Sequences., , , , and . CoRR, (2021)A Deep Attentive Convolutional Neural Network for Automatic Cortical Plate Segmentation in Fetal MRI., , , , , , , , , and . CoRR, (2020)Melanoma Recognition in Dermoscopy Images via Aggregated Deep Convolutional Features., , , , , , , and . IEEE Trans. Biomed. Eng., 66 (4): 1006-1016 (2019)AutoPath: Image-Specific Inference for 3D Segmentation., , , and . Frontiers Neurorobotics, (2020)Learning based automatic head detection and measurement from fetal ultrasound images via prior knowledge and imaging parameters., , , , , , and . ISBI, page 772-775. IEEE, (2013)Cascaded Fully Convolutional Networks for automatic prenatal ultrasound image segmentation., , , , , and . ISBI, page 663-666. IEEE, (2017)Segmentation and Recovery of Pathological MR Brain Images Using Transformed Low-Rank and Structured Sparse Decomposition., , , and . ISBI, page 1878-1881. IEEE, (2019)A method for real-time control of thin film composition using OES and XPS., , , , , and . ACC, page 1320-1327. IEEE, (2003)Learn Fine-grained Adaptive Loss for Multiple Anatomical Landmark Detection in Medical Images., , , , , , , , , and . CoRR, (2021)Learning Visual Context for Group Activity Recognition., and . AAAI, page 3261-3269. AAAI Press, (2021)