about
Evaluation of prostate segmentation algorithms for MRI: the PROMISE12 challengeProstate Cancer: The European Society of Urogenital Radiology Prostate Imaging Reporting and Data System Criteria for Predicting Extraprostatic Extension by Using 3-T Multiparametric MR Imaging.Quantitative identification of magnetic resonance imaging features of prostate cancer response following laser ablation and radical prostatectomyUsing deep learning to segment breast and fibroglandular tissue in MRI volumes.Computer-extracted Features Can Distinguish Noncancerous Confounding Disease from Prostatic Adenocarcinoma at Multiparametric MR Imaging.Deep learning as a tool for increased accuracy and efficiency of histopathological diagnosis.MAGE expression in head and neck squamous cell carcinoma primary tumors, lymph node metastases and respective recurrences-implications for immunotherapy.Interpatient variation in normal peripheral zone apparent diffusion coefficient: effect on the prediction of prostate cancer aggressiveness.Multiparametric Magnetic Resonance Imaging for Discriminating Low-Grade From High-Grade Prostate Cancer.Large scale deep learning for computer aided detection of mammographic lesions.Automated multistructure atlas-assisted detection of lymph nodes using pelvic MR lymphography in prostate cancer patients.Pulmonary Nodule Detection in CT Images: False Positive Reduction Using Multi-View Convolutional Networks.Stain Specific Standardization of Whole-Slide Histopathological Images.Clinical evaluation of a computer-aided diagnosis system for determining cancer aggressiveness in prostate MRI.Intranodal signal suppression in pelvic MR lymphography of prostate cancer patients: a quantitative comparison of ferumoxtran-10 and ferumoxytol.Evaluation of tongue squamous cell carcinoma resection margins using ex-vivo MR.Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer.Automated Detection of DCIS in Whole-Slide H&E Stained Breast Histopathology Images.Context-aware stacked convolutional neural networks for classification of breast carcinomas in whole-slide histopathology images.Computer-aided detection of prostate cancer in MRI.1399 H&E-stained sentinel lymph node sections of breast cancer patients: the CAMELYON dataset.Epithelium segmentation using deep learning in H&E-stained prostate specimens with immunohistochemistry as reference standardA pattern recognition approach to zonal segmentation of the prostate on MRIRobust and accurate quantification of biomarkers of immune cells in lung cancer micro-environment using deep convolutional neural networksSimulation of nodules and diffuse infiltrates in chest radiographs using CT templatesMachine Learning Compared With Pathologist Assessment-ReplyWhole-Slide Mitosis Detection in H&E Breast Histology Using PHH3 as a Reference to Train Distilled Stain-Invariant Convolutional NetworksNo pixel-level annotations neededFrom Detection of Individual Metastases to Classification of Lymph Node Status at the Patient Level: The CAMELYON17 ChallengeLymph node detection in MR Lymphography: false positive reduction using multi-view convolutional neural networksComputer aided quantification of intratumoral stroma yields an independent prognosticator in rectal cancerResolution-agnostic tissue segmentation in whole-slide histopathology images with convolutional neural networksState-of-the-Art Deep Learning in Cardiovascular Image AnalysisAutomated deep-learning system for Gleason grading of prostate cancer using biopsies: a diagnostic studyA Single-Arm, Multicenter Validation Study of Prostate Cancer Localization and Aggressiveness With a Quantitative Multiparametric Magnetic Resonance Imaging ApproachQuantifying the effects of data augmentation and stain color normalization in convolutional neural networks for computational pathologyLearning to detect lymphocytes in immunohistochemistry with deep learning
P50
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P50
description
hulumtues
@sq
researcher
@en
wetenschapper
@nl
հետազոտող
@hy
name
Geert Litjens
@ast
Geert Litjens
@en
Geert Litjens
@es
Geert Litjens
@nl
Geert Litjens
@sl
type
label
Geert Litjens
@ast
Geert Litjens
@en
Geert Litjens
@es
Geert Litjens
@nl
Geert Litjens
@sl
prefLabel
Geert Litjens
@ast
Geert Litjens
@en
Geert Litjens
@es
Geert Litjens
@nl
Geert Litjens
@sl
P1053
A-2319-2016
P106
P21
P31
P3829
P496
0000-0003-1554-1291
P569
1985-01-01T00:00:00Z