[HTML][HTML] The impact of pre-and post-image processing techniques on deep learning frameworks: A comprehensive review for digital pathology image analysis
Recently, deep learning frameworks have rapidly become the main methodology for
analyzing medical images. Due to their powerful learning ability and advantages in dealing …
analyzing medical images. Due to their powerful learning ability and advantages in dealing …
A comprehensive review of computer-aided whole-slide image analysis: from datasets to feature extraction, segmentation, classification and detection approaches
With the development of Computer-aided Diagnosis (CAD) and image scanning techniques,
Whole-slide Image (WSI) scanners are widely used in the field of pathological diagnosis …
Whole-slide Image (WSI) scanners are widely used in the field of pathological diagnosis …
Whole slide images based cancer survival prediction using attention guided deep multiple instance learning networks
Traditional image-based survival prediction models rely on discriminative patch labeling
which make those methods not scalable to extend to large datasets. Recent studies have …
which make those methods not scalable to extend to large datasets. Recent studies have …
Going deep in medical image analysis: concepts, methods, challenges, and future directions
Medical image analysis is currently experiencing a paradigm shift due to deep learning. This
technology has recently attracted so much interest of the Medical Imaging Community that it …
technology has recently attracted so much interest of the Medical Imaging Community that it …
Neural image compression for gigapixel histopathology image analysis
We propose Neural Image Compression (NIC), a two-step method to build convolutional
neural networks for gigapixel image analysis solely using weak image-level labels. First …
neural networks for gigapixel image analysis solely using weak image-level labels. First …
RMDL: Recalibrated multi-instance deep learning for whole slide gastric image classification
The whole slide histopathology images (WSIs) play a critical role in gastric cancer diagnosis.
However, due to the large scale of WSIs and various sizes of the abnormal area, how to …
However, due to the large scale of WSIs and various sizes of the abnormal area, how to …
A survey on artificial intelligence in histopathology image analysis
The increasing adoption of the whole slide image (WSI) technology in histopathology has
dramatically transformed pathologists' workflow and allowed the use of computer systems in …
dramatically transformed pathologists' workflow and allowed the use of computer systems in …
A deep learning approach for colonoscopy pathology WSI analysis: accurate segmentation and classification
Colorectal cancer (CRC) is one of the most life-threatening malignancies. Colonoscopy
pathology examination can identify cells of early-stage colon tumors in small tissue image …
pathology examination can identify cells of early-stage colon tumors in small tissue image …
Context-aware convolutional neural network for grading of colorectal cancer histology images
Digital histology images are amenable to the application of convolutional neural networks
(CNNs) for analysis due to the sheer size of pixel data present in them. CNNs are generally …
(CNNs) for analysis due to the sheer size of pixel data present in them. CNNs are generally …
Histosegnet: Semantic segmentation of histological tissue type in whole slide images
L Chan, MS Hosseini, C Rowsell… - Proceedings of the …, 2019 - openaccess.thecvf.com
In digital pathology, tissue slides are scanned into Whole Slide Images (WSI) and
pathologists first screen for diagnostically-relevant Regions of Interest (ROIs) before …
pathologists first screen for diagnostically-relevant Regions of Interest (ROIs) before …