Review The Cancer Genome Atlas (TCGA): an immeasurable source of knowledge
K Tomczak, P Czerwińska… - Contemporary Oncology …, 2015 - termedia.pl
The Cancer Genome Atlas (TCGA) is a public funded project that aims to catalogue and
discover major cancer-causing genomic alterations to create a comprehensive “atlas” of …
discover major cancer-causing genomic alterations to create a comprehensive “atlas” of …
Robust nucleus/cell detection and segmentation in digital pathology and microscopy images: a comprehensive review
Digital pathology and microscopy image analysis is widely used for comprehensive studies
of cell morphology or tissue structure. Manual assessment is labor intensive and prone to …
of cell morphology or tissue structure. Manual assessment is labor intensive and prone to …
A multi-organ nucleus segmentation challenge
Generalized nucleus segmentation techniques can contribute greatly to reducing the time to
develop and validate visual biomarkers for new digital pathology datasets. We summarize …
develop and validate visual biomarkers for new digital pathology datasets. We summarize …
A dataset and a technique for generalized nuclear segmentation for computational pathology
Nuclear segmentation in digital microscopic tissue images can enable extraction of high-
quality features for nuclear morphometrics and other analysis in computational pathology …
quality features for nuclear morphometrics and other analysis in computational pathology …
MoNuSAC2020: A multi-organ nuclei segmentation and classification challenge
Detecting various types of cells in and around the tumor matrix holds a special significance
in characterizing the tumor micro-environment for cancer prognostication and research …
in characterizing the tumor micro-environment for cancer prognostication and research …
Stacked sparse autoencoder (SSAE) for nuclei detection on breast cancer histopathology images
Automated nuclear detection is a critical step for a number of computer assisted pathology
related image analysis algorithms such as for automated grading of breast cancer tissue …
related image analysis algorithms such as for automated grading of breast cancer tissue …
Pannuke: an open pan-cancer histology dataset for nuclei instance segmentation and classification
J Gamper, N Alemi Koohbanani, K Benet… - Digital Pathology: 15th …, 2019 - Springer
In this work we present an experimental setup to semi automatically obtain exhaustive nuclei
labels across 19 different tissue types, and therefore construct a large pan-cancer dataset for …
labels across 19 different tissue types, and therefore construct a large pan-cancer dataset for …
An automatic learning-based framework for robust nucleus segmentation
Computer-aided image analysis of histopathology specimens could potentially provide
support for early detection and improved characterization of diseases such as brain tumor …
support for early detection and improved characterization of diseases such as brain tumor …
Accurate segmentation of cervical cytoplasm and nuclei based on multiscale convolutional network and graph partitioning
In this paper, a multiscale convolutional network (MSCN) and graph-partitioning-based
method is proposed for accurate segmentation of cervical cytoplasm and nuclei. Specifically …
method is proposed for accurate segmentation of cervical cytoplasm and nuclei. Specifically …
The digital slide archive: a software platform for management, integration, and analysis of histology for cancer research
Tissue-based cancer studies can generate large amounts of histology data in the form of
glass slides. These slides contain important diagnostic, prognostic, and biological …
glass slides. These slides contain important diagnostic, prognostic, and biological …