Deep convolutional neural network-based lymph node metastasis prediction for colon cancer using histopathological images
MS Kwak, HH Lee, JM Yang, JM Cha, JW Jeon… - Frontiers in …, 2021 - frontiersin.org
… cancer. We aimed to develop accurate histopathological features for LNM in colon cancer. …
model to distinguish the cancer tissue component of colon cancer using data from the tissue …
model to distinguish the cancer tissue component of colon cancer using data from the tissue …
Deep learning for magnification independent breast cancer histopathology image classification
N Bayramoglu, J Kannala… - 2016 23rd International …, 2016 - ieeexplore.ieee.org
… In this paper, we propose to classify breast cancer histopathology images independent of
their magnifications. We present the classification performance of a deep learning method on …
their magnifications. We present the classification performance of a deep learning method on …
Detecting lung cancer from histopathological images using convolution neural network
… The dataset used in this study contains 15000 lung histopathology images. This dataset is
… lung cancer using histopathological images. The whole dataset consisted of 15000 images …
… lung cancer using histopathological images. The whole dataset consisted of 15000 images …
Detection of mitotic cells in breast cancer histopathological images using deep versus handcrafted features
… mitosis from breast cancer histopathological images, which is one of the important criteria
in breast cancer grading. In this study, histopathological images of breast cancer shared in the …
in breast cancer grading. In this study, histopathological images of breast cancer shared in the …
Detecting mitotic figures in breast cancer histopathology images
… tissue, since this is the histological stain routinely used with each case. The advent of
whole-slide imaging has brought renewed interest in analysis of histopathology images. Recently, …
whole-slide imaging has brought renewed interest in analysis of histopathology images. Recently, …
A neural pathomics framework for classifying colorectal cancer histopathology images based on wavelet multi-scale texture analysis
… from the analysis of digitized histopathology images with the use of image analysis methods
… As in radiomics, the main image processing methodology used to extract a large number of …
… As in radiomics, the main image processing methodology used to extract a large number of …
A comparative study of CNN, BoVW and LBP for classification of histopathological images
… of histopathological images. We introduce a new dataset, KIMIA Path960, that contains 960
histopathology images … image descriptors for search and classification in complex medical …
histopathology images … image descriptors for search and classification in complex medical …
Convolution neural networks for diagnosing colon and lung cancer histopathological images
S Mangal, A Chaurasia, A Khajanchi - arXiv preprint arXiv:2009.03878, 2020 - arxiv.org
… Image classification is a challenging task for the visual content, particularly microscopic images
for example histopathological images … textures present in histopathology of images. Deep …
for example histopathological images … textures present in histopathology of images. Deep …
[HTML][HTML] Deep learning of histopathology images at the single cell level
… In this review we focus on machine learning-based digital histopathology image analysis …
of histopathological analyses that machine learning can operate within: whole slide image (WSI…
of histopathological analyses that machine learning can operate within: whole slide image (WSI…
Deep manifold preserving autoencoder for classifying breast cancer histopathological images
… In this section, we conduct some experiments on a public breast cancer histopathological
image database to evaluate the performance of our proposed method. Seven widelyused …
image database to evaluate the performance of our proposed method. Seven widelyused …