Titlebook: Machine Learning in Medical Imaging; 10th International W Heung-Il Suk,Mingxia Liu,Chunfeng Lian Conference proceedings 2019 Springer Natur

忍受

大廳

Novel Bi-directional Images Synthesis Based on WGAN-GP with GMM-Based Noise Generation,ral popular deep learning-based models both qualitatively and quantitatively. The superiority of the new model is substantiated based on a series of rigorous experiments using a multi-modal MRI database composed of 355 real demented patients in this study, from the statistical perspective.

LUDE

刺耳

aneurysm

Curmudgeon

Advancing Pancreas Segmentation in Multi-protocol MRI Volumes Using Hausdorff-Sine Loss Function, in magnetic resonance imaging (MRI) remains challenging due to high inter-patient variability. Also, the resolution and speed of MRI scanning present artefacts that blur the pancreas boundaries between overlapping anatomical structures. This paper proposes a dual-stage automatic segmentation method

Herpetologist

WSI-Net: Branch-Based and Hierarchy-Aware Network for Segmentation and Classification of Breast Hisches from the WSI into three types, including non-malignant, ductal carcinoma in situ, and invasive ductal carcinoma. It adds a parallel classification branch on the top of the low layer of a semantic segmentation model DeepLab. This branch can fast identify and discard those non-malignant patches i

Hypopnea

visceral-fat

MSAFusionNet: Multiple Subspace Attention Based Deep Multi-modal Fusion Network,as not been fully studied in the field of deep learning within such a context. In this paper, we address the task of end-to-end segmentation based on multi-modal data and propose a novel deep learning framework, multiple subspace attention-based deep multi-modal fusion network (referred to as MSAFus

花爭(zhēng)吵

DCCL: A Benchmark for Cervical Cytology Analysis, fields, including cervical cytology, a large well-annotated benchmark dataset remains missing. In this paper, we introduce by far the largest cervical cytology dataset, called Deep Cervical Cytological Lesions (referred to as DCCL). DCCL contains 14,432 image patches with around . pixels cropped fr