Results 31 to 40 of about 259,250 (296)

Predicting survival from colorectal cancer histology slides using deep learning: A retrospective multicenter study [PDF]

open access: yes, 2019
BACKGROUND: For virtually every patient with colorectal cancer (CRC), hematoxylin-eosin (HE)-stained tissue slides are available. These images contain quantitative information, which is not routinely used to objectively extract prognostic biomarkers.
Brenner, H.   +17 more
core   +2 more sources

Research on the Auxiliary Classification and Diagnosis of Lung Cancer Subtypes Based on Histopathological Images

open access: yesIEEE Access, 2021
Lung cancer (LC) is one of the most serious cancers threatening human health. Histopathological examination is the gold standard for qualitative and clinical staging of lung tumors.
Min Li   +11 more
doaj   +1 more source

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images [PDF]

open access: yes, 2018
Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA
Abdel-Rahman, Mohamed H.   +740 more
core   +3 more sources

Enhanced Sharp-Gan for Histopathology Image Synthesis

open access: yes2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI), 2023
Histopathology image synthesis aims to address the data shortage issue in training deep learning approaches for accurate cancer detection. However, existing methods struggle to produce realistic images that have accurate nuclei boundaries and less artifacts, which limits the application in downstream tasks. To address the challenges, we propose a novel
Butte, Sujata   +3 more
openaire   +3 more sources

Gland segmentation in prostate histopathological images [PDF]

open access: yesJournal of Medical Imaging, 2017
Glandular structural features are important for the tumor pathologist in the assessment of cancer malignancy of prostate tissue slides. The varying shapes and sizes of glands combined with the tedious manual observation task can result in inaccurate assessment. There are also discrepancies and low-level agreement among pathologists, especially in cases
Singh, Malay   +5 more
openaire   +3 more sources

Impact of data preprocessing and augmentation on tumor core segmentation using convolutional neural networks

open access: yesКомпьютерная оптика
The relevance of detecting and treating breast cancer in the early stages remains high. In 2020, more than 65,000 new cases of breast cancer were registered, with an average annual growth rate being 2%.
N.S. Buravsky, E.Y. Kostyuchenko
doaj   +1 more source

DFDL: Discriminative Feature-oriented Dictionary Learning for Histopathological Image Classification

open access: yes, 2015
In histopathological image analysis, feature extraction for classification is a challenging task due to the diversity of histology features suitable for each problem as well as presence of rich geometrical structure.
Monga, Vishal   +4 more
core   +1 more source

CRISPR/Cas9 mediated knockout of rb1 and rbl1 leads to rapid and penetrant retinoblastoma development in Xenopus tropicalis [PDF]

open access: yes, 2016
Retinoblastoma is a pediatric eye tumor in which bi-allelic inactivation of the Retinoblastoma 1 (RB1) gene is the initiating genetic lesion. Although recently curative rates of retinoblastoma have increased, there are at this time no molecular targeted ...
Boel, Annekatrien   +12 more
core   +2 more sources

Meningioangiomatosis: Clinical, Imaging, and Histopathologic Characteristics

open access: yesJournal of Clinical Imaging Science, 2020
Meningioangiomatosis is a rare benign lesion involving the central nervous system. Radiographic appearance can be highly variable which makes pre-operative diagnosis difficult. In this report, we describe meningioangiomatosis in a previously healthy 17-year-old woman who presented with seizures and continued headache and dizziness.
Makary, Mina S.   +3 more
openaire   +2 more sources

Deep-Learning for Classification of Colorectal Polyps on Whole-Slide Images

open access: yes, 2017
Histopathological characterization of colorectal polyps is an important principle for determining the risk of colorectal cancer and future rates of surveillance for patients. This characterization is time-intensive, requires years of specialized training,
Hassanpour, Saeed   +7 more
core   +2 more sources

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