Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
Breast cancer histopathology image analysis: A review
This paper presents an overview of methods that have been proposed for the analysis of
breast cancer histopathology images. This research area has become particularly relevant …
breast cancer histopathology images. This research area has become particularly relevant …
Mitosis detection techniques in H&E stained breast cancer pathological images: A comprehensive review
Quantifying mitosis in pathological sections is of great significance in the pathological
diagnosis of breast cancer as it is used to evaluate the aggressiveness of the tumor and to …
diagnosis of breast cancer as it is used to evaluate the aggressiveness of the tumor and to …
Mitosis detection in breast cancer histology images with deep neural networks
We use deep max-pooling convolutional neural networks to detect mitosis in breast
histology images. The networks are trained to classify each pixel in the images, using as …
histology images. The networks are trained to classify each pixel in the images, using as …
Assessment of algorithms for mitosis detection in breast cancer histopathology images
The proliferative activity of breast tumors, which is routinely estimated by counting of mitotic
figures in hematoxylin and eosin stained histology sections, is considered to be one of the …
figures in hematoxylin and eosin stained histology sections, is considered to be one of the …
Mitosis detection in breast cancer histology images via deep cascaded networks
The number of mitoses per tissue area gives an important aggressiveness indication of the
invasive breast carcinoma. However, automatic mitosis detection in histology images …
invasive breast carcinoma. However, automatic mitosis detection in histology images …
Efficient deep learning model for mitosis detection using breast histopathology images
Mitosis detection is one of the critical factors of cancer prognosis, carrying significant
diagnostic information required for breast cancer grading. It provides vital clues to estimate …
diagnostic information required for breast cancer grading. It provides vital clues to estimate …
Weakly supervised mitosis detection in breast histopathology images using concentric loss
Develo** new deep learning methods for medical image analysis is a prevalent research
topic in machine learning. In this paper, we propose a deep learning scheme with a novel …
topic in machine learning. In this paper, we propose a deep learning scheme with a novel …
DeepMitosis: Mitosis detection via deep detection, verification and segmentation networks
Mitotic count is a critical predictor of tumor aggressiveness in the breast cancer diagnosis.
Nowadays mitosis counting is mainly performed by pathologists manually, which is …
Nowadays mitosis counting is mainly performed by pathologists manually, which is …
Two-phase deep convolutional neural network for reducing class skewness in histopathological images based breast cancer detection
Different types of breast cancer are affecting lives of women across the world. Common
types include Ductal carcinoma in situ (DCIS), Invasive ductal carcinoma (IDC), Tubular …
types include Ductal carcinoma in situ (DCIS), Invasive ductal carcinoma (IDC), Tubular …
Novel architecture with selected feature vector for effective classification of mitotic and non-mitotic cells in breast cancer histology images
The paper focuses on the detection of mitosis in breast cancer. Detection methods in vogue
rely heavily on visual inspection and assessment of histology images by trained …
rely heavily on visual inspection and assessment of histology images by trained …