Papers Color Normalization
“Color Normalization” 태그가 달린 논문 23편 · 필터 해제
SiliCoN: Simultaneous Nuclei Segmentation and Color Normalization of Histological Images
Segmentation of nuclei regions from histological images is an important task for automated computer-aided analysis of histological images, particularly in the presence of impermissible color variation in the color appear…
Color NormalizationSegmentationNCT-CRC-HE: Not All Histopathological Datasets Are Equally Useful
Numerous deep learning-based solutions have been proposed for histopathological image analysis over the past years. While they usually demonstrate exceptionally high accuracy, one key question is whether their precision …
AllColor NormalizationImpact of Stain Variation and Color Normalization for Prognostic Predictions in Pathology
In recent years, deep neural networks (DNNs) have demonstrated remarkable performance in pathology applications, potentially even outperforming expert pathologists due to their ability to learn subtle features from large…
Color NormalizationGenerative Adversarial NetworkSelf-supervised Vision Transformer are Scalable Generative Models for Domain Generalization
Despite notable advancements, the integration of deep learning (DL) techniques into impactful clinical applications, particularly in the realm of digital histopathology, has been hindered by challenges associated with ac…
Color NormalizationData AugmentationDomain GeneralizationEpidermaQuant: Unsupervised detection and quantification of epidermal differentiation markers on H-DAB-stained images of reconstructed human epidermis
The integrity of the reconstructed human epidermis generated in vitro could be assessed using histological analyses combined with immunohistochemical staining of keratinocyte differentiation markers. Computer-based analy…
ClusteringColor NormalizationColor Deconvolution applied to Domain Adaptation in HER2 histopathological images
Breast cancer early detection is crucial for improving patient outcomes. The Institut Catal\`a de la Salut (ICS) has launched the DigiPatICS project to develop and implement artificial intelligence algorithms to assist w…
Color NormalizationDomain AdaptationStyle TransferNeural Preset for Color Style Transfer
In this paper, we present a Neural Preset technique to address the limitations of existing color style transfer methods, including visual artifacts, vast memory requirement, and slow style switching speed. Our method is …
4kColor NormalizationImage DehazingImage Enhancement+3A Morphology Focused Diffusion Probabilistic Model for Synthesis of Histopathology Images
Visual microscopic study of diseased tissue by pathologists has been the cornerstone for cancer diagnosis and prognostication for more than a century. Recently, deep learning methods have made significant advances in the…
Color NormalizationQuantifying the effect of color processing on blood and damaged tissue detection in Whole Slide Images
Histological tissue examination has been a longstanding practice for cancer diagnosis where pathologists identify the presence of tumors on glass slides. Slides acquired from laboratory routine may contain unintentional …
Artifact DetectionBinary ClassificationBlood DetectionColor Normalization+4Adversarial Stain Transfer to Study the Effect of Color Variation on Cell Instance Segmentation
Stain color variation in histological images, caused by a variety of factors, is a challenge not only for the visual diagnosis of pathologists but also for cell segmentation algorithms. To eliminate the color variation, …
Cell SegmentationColor NormalizationInstance SegmentationSegmentation+1Stain Normalized Breast Histopathology Image Recognition using Convolutional Neural Networks for Cancer Detection
Computer assisted diagnosis in digital pathology is becoming ubiquitous as it can provide more efficient and objective healthcare diagnostics. Recent advances have shown that the convolutional Neural Network (CNN) archit…
Binary ClassificationBreast Cancer DetectionColor NormalizationDiagnostic+1Structure-Preserving Multi-Domain Stain Color Augmentation using Style-Transfer with Disentangled Representations
In digital pathology, different staining procedures and scanners cause substantial color variations in whole-slide images (WSIs), especially across different laboratories. These color shifts result in a poor generalizati…
Color NormalizationGenerative Adversarial NetworkImage-to-Image TranslationStyle Transfer+1Accurate Cell Segmentation in Digital Pathology Images via Attention Enforced Networks
Automatic cell segmentation is an essential step in the pipeline of computer-aided diagnosis (CAD), such as the detection and grading of breast cancer. Accurate segmentation of cells can not only assist the pathologists …
Cell SegmentationColor NormalizationSegmentationFast, Self Supervised, Fully Convolutional Color Normalization of H&E Stained Images
Performance of deep learning algorithms decreases drastically if the data distributions of the training and testing sets are different. Due to variations in staining protocols, reagent brands, and habits of technicians, …
Color NormalizationDeep LearningStructure Preserving Stain Normalization of Histopathology Images Using Self-Supervised Semantic Guidance
Although generative adversarial network (GAN) based style transfer is state of the art in histopathology color-stain normalization, they do not explicitly integrate structural information of tissues. We propose a self-su…
Color NormalizationGenerative Adversarial NetworkSegmentationStyle TransferA deep learning based multiscale approach to segment cancer area in liver whole slide image
This paper addresses the problem of liver cancer segmentation in Whole Slide Image (WSI). We propose a multi-scale image processing method based on automatic end-to-end deep neural network algorithm for segmentation of c…
Color NormalizationSegmentationQuantifying the effects of data augmentation and stain color normalization in convolutional neural networks for computational pathology
Stain variation is a phenomenon observed when distinct pathology laboratories stain tissue slides that exhibit similar but not identical color appearance. Due to this color shift between laboratories, convolutional neura…
Color NormalizationData AugmentationFast GPU-Enabled Color Normalization for Digital Pathology
Normalizing unwanted color variations due to differences in staining processes and scanner responses has been shown to aid machine learning in computational pathology. Of the several popular techniques for color normaliz…
Color NormalizationGPUwhole slide imagesData-Driven Color Augmentation Techniques for Deep Skin Image Analysis
Dermoscopic skin images are often obtained with different imaging devices, under varying acquisition conditions. In this work, instead of attempting to perform intensity and color normalization, we propose to leverage co…
Color ConstancyColor NormalizationData AugmentationLesion Classification+3Adaptive Gray World-Based Color Normalization of Thin Blood Film Images
This paper presents an effective color normalization method for thin blood film images of peripheral blood specimens. Thin blood film images can easily be separated to foreground (cell) and background (plasma) parts. The…
Color Normalization