Results 31 to 40 of about 256,649 (274)

A Deep Learning Framework for the Prediction and Diagnosis of Ovarian Cancer in Pre- and Post-Menopausal Women

open access: yesDiagnostics, 2023
Ovarian cancer ranks as the fifth leading cause of cancer-related mortality in women. Late-stage diagnosis (stages III and IV) is a major challenge due to the often vague and inconsistent initial symptoms.
Blessed Ziyambe   +9 more
doaj   +1 more source

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

OpenHI2 — Open source histopathological image platform [PDF]

open access: yes2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2019
Transition from conventional to digital pathology requires a new category of biomedical informatic infrastructure which could facilitate delicate pathological routine. Pathological diagnoses are sensitive to many external factors and is known to be subjective.
Puttapirat, Pargorn   +9 more
openaire   +2 more sources

Prospects for Theranostics in Neurosurgical Imaging: Empowering Confocal Laser Endomicroscopy Diagnostics via Deep Learning [PDF]

open access: yes, 2018
Confocal laser endomicroscopy (CLE) is an advanced optical fluorescence imaging technology that has the potential to increase intraoperative precision, extend resection, and tailor surgery for malignant invasive brain tumors because of its subcellular ...
Evgenii Belykh   +8 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

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

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

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