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Deep neural network models for computational histopathology: A survey
Histopathological images contain rich phenotypic information that can be used to monitor
underlying mechanisms contributing to disease progression and patient survival outcomes …
underlying mechanisms contributing to disease progression and patient survival outcomes …
A survey on deep learning in medical image analysis
Deep learning algorithms, in particular convolutional networks, have rapidly become a
methodology of choice for analyzing medical images. This paper reviews the major deep …
methodology of choice for analyzing medical images. This paper reviews the major deep …
[HTML][HTML] Cellvit: Vision transformers for precise cell segmentation and classification
Nuclei detection and segmentation in hematoxylin and eosin-stained (H&E) tissue images
are important clinical tasks and crucial for a wide range of applications. However, it is a …
are important clinical tasks and crucial for a wide range of applications. However, it is a …
Medical image analysis based on deep learning approach
Medical imaging plays a significant role in different clinical applications such as medical
procedures used for early detection, monitoring, diagnosis, and treatment evaluation of …
procedures used for early detection, monitoring, diagnosis, and treatment evaluation of …
Skin lesion segmentation via generative adversarial networks with dual discriminators
B Lei, Z **, yet challenging topic in medical
image computing concerned with analyzing digitized cytology images by computer-aided …
image computing concerned with analyzing digitized cytology images by computer-aided …
A review of image analysis and machine learning techniques for automated cervical cancer screening from pap-smear images
Abstract Background and Objective Early diagnosis and classification of a cancer type can
help facilitate the subsequent clinical management of the patient. Cervical cancer ranks as …
help facilitate the subsequent clinical management of the patient. Cervical cancer ranks as …
Micro-Net: A unified model for segmentation of various objects in microscopy images
Object segmentation and structure localization are important steps in automated image
analysis pipelines for microscopy images. We present a convolution neural network (CNN) …
analysis pipelines for microscopy images. We present a convolution neural network (CNN) …
Donet: Deep de-overlap** network for cytology instance segmentation
Cell instance segmentation in cytology images has significant importance for biology
analysis and cancer screening, while remains challenging due to 1) the extensive …
analysis and cancer screening, while remains challenging due to 1) the extensive …