Ink removal from histopathology whole slide images by combining classification, detection and image generation models

Ink removal from histopathology whole slide images by combining classification, detection and image generation models

Histopathology slides are routinely marked by pathologists using permanent ink markers that should not be removed as they form part of the medical record. Often tumour regions are marked up for the purpose of highlighting features or other downstream processing such an gene sequencing. Once digitise...

Bibliografske podrobnosti
Main Authors:	Ali, S, Alham, N, Verrill, C, Rittscher, J
Format:	Journal article
Izdano:	IEEE 2019

Podobne knjige/članki

Improving whole slide segmentation through visual context: a systematic study
od: Sirinukunwattana, K, et al.
Izdano: (2018)

Artificial intelligence-based quality assessment of histopathology whole-slide images within a clinical workflow: assessment of 'pathprofiler' in a diagnostic pathology setting
od: Browning, L, et al.
Izdano: (2024)

Transfer Learning Approach for Classification of Histopathology Whole Slide Images
od: Shakil Ahmed, et al.
Izdano: (2021-08-01)

Unsupervised Domain Adaptation for Classification of Histopathology Whole-Slide Images
od: Jian Ren, et al.
Izdano: (2019-05-01)

Artificial Intelligence-Based Quality Assessment of Histopathology Whole-Slide Images within a Clinical Workflow: Assessment of ‘PathProfiler’ in a Diagnostic Pathology Setting
od: Lisa Browning, et al.
Izdano: (2024-05-01)

Anonymization of whole slide images in histopathology for research and education
od: Tom Bisson, et al.
Izdano: (2023-05-01)

Deep learning-enabled classification of kidney allograft rejection on whole slide histopathologic images
od: Yongrong Ye, et al.
Izdano: (2024-07-01)

A deep learning framework for automated classification of histopathological kidney whole-slide images
od: Hisham A. Abdeltawab, et al.
Izdano: (2022-01-01)

Aligning knowledge concepts to whole slide images for precise histopathology image analysis
od: Weiqin Zhao, et al.
Izdano: (2024-12-01)

Validation of histopathology foundation models through whole slide image retrieval
od: Saghir Alfasly, et al.
Izdano: (2025-02-01)

Nuclei-level prior knowledge constrained multiple instance learning for breast histopathology whole slide image classification
od: Xunping Wang, et al.
Izdano: (2024-06-01)

Deep Learning-Based Classification of Uterine Cervical and Endometrial Cancer Subtypes from Whole-Slide Histopathology Images
od: JaeYen Song, et al.
Izdano: (2022-10-01)

A multi-center performance assessment for automated histopathological classification and grading of glioma using whole slide images
od: Lei Jin, et al.
Izdano: (2023-11-01)

Accurate diagnosis of lymphoma on whole-slide histopathology images using deep learning
od: Charlotte Syrykh, et al.
Izdano: (2020-05-01)

Optimized JPEG 2000 compression for efficient storage of histopathological whole-Slide images
od: Henrik Helin, et al.
Izdano: (2018-01-01)

Detection of Breast Cancer From Whole Slide Histopathological Images Using Deep Multiple Instance CNN
od: Kausik Das, et al.
Izdano: (2020-01-01)

Resolution-agnostic tissue segmentation in whole-slide histopathology images with convolutional neural networks
od: Péter Bándi, et al.
Izdano: (2019-12-01)

Deep learning based registration of serial whole-slide histopathology images in different stains
od: Mousumi Roy, et al.
Izdano: (2023-01-01)

A High-Performance System for Robust Stain Normalization of Whole-Slide Images in Histopathology
od: Andreea Anghel, et al.
Izdano: (2019-09-01)

An efficient context-aware approach for whole-slide image classification
od: Hongru Shen, et al.
Izdano: (2023-12-01)

Deep learning for classification of colorectal polyps on whole-slide images
od: Bruno Korbar, et al.
Izdano: (2017-01-01)

Eliminating tissue-fold artifacts in histopathological whole-slide images for improved image-based prediction of cancer grade
od: Sonal Kothari, et al.
Izdano: (2013-01-01)

Deep learning-based breast cancer grading and survival analysis on whole-slide histopathology images
od: Suzanne C. Wetstein, et al.
Izdano: (2022-09-01)

Potential quality pitfalls of digitalized whole slide image of breast pathology in routine practice
od: Atallah, NM, et al.
Izdano: (2021)

Benchmarking histopathology foundation models for ovarian cancer bevacizumab treatment response prediction from whole slide images
od: Mayur Mallya, et al.
Izdano: (2025-02-01)

Enhanced Multi-Class Breast Cancer Classification from Whole-Slide Histopathology Images Using a Proposed Deep Learning Model
od: Adnan Rafiq, et al.
Izdano: (2025-02-01)

Deep Learning Classification of Colorectal Lesions Based on Whole Slide Images
od: Sergey A. Soldatov, et al.
Izdano: (2022-10-01)

Publicly available datasets of breast histopathology H&E whole-slide images: A scoping review
od: Masoud Tafavvoghi, et al.
Izdano: (2024-12-01)

Histopathologic Patterns of Nervous System Tumors Based on Computer Vision Methods and Whole Slide Imaging (WSI)
od: Slawomir Walkowski, et al.
Izdano: (2012-01-01)

Deep learning to assess microsatellite instability directly from histopathological whole slide images in endometrial cancer
od: Ching-Wei Wang, et al.
Izdano: (2024-05-01)

A correlation graph attention network for classifying chromosomal instabilities from histopathology whole-slide images
od: Liangliang Liu, et al.
Izdano: (2023-06-01)

Predicting oncogene mutations of lung cancer using deep learning and histopathologic features on whole-slide images
od: Naofumi Tomita, et al.
Izdano: (2022-10-01)

Precise identification of cell and tissue features important for histopathologic diagnosis by a whole slide imaging system
od: Thomas W Bauer, et al.
Izdano: (2020-01-01)

Verification and validation of digital pathology (whole slide imaging) for primary histopathological diagnosis: All wales experience
od: M Babawale, et al.
Izdano: (2021-01-01)

Deep learning-based histopathological segmentation for whole slide images of colorectal cancer in a compressed domain
od: Hyeongsub Kim, et al.
Izdano: (2021-11-01)

The importance of eSlide macro images for primary diagnosis with whole slide imaging
od: Filippo Fraggetta, et al.
Izdano: (2018-01-01)

An automated blur detection method for histological whole slide imaging.
od: Xavier Moles Lopez, et al.
Izdano: (2013-01-01)

Weakly supervised detection and classification of basal cell carcinoma using graph-transformer on whole slide images
od: Filmon Yacob, et al.
Izdano: (2023-05-01)

Validation of Whole Slide Imaging in Pathology
od: Liron Pantanowitz
Izdano: (2014-01-01)

Whole slide imaging for educational purposes
od: Liron Pantanowitz, et al.
Izdano: (2012-01-01)