ICCVB

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ICCVB

metasource: BiŌkeanós-Medsourcing
version: 0.0.1:2022-11-04T13:34:25.975929

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I2CVB

metasource: BiŌkeanós-Medsourcing
version: 0.0.1:2022-11-04T13:34:25.975929

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Initiative for Collaborative Computer Vision Benchmarking

metasource: BiŌkeanós-Medsourcing
version: 0.0.1:2022-11-04T13:34:25.975929

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Other names: I2CVB, Initiative for Collaborative Computer Vision Benchmarking

A that gathered imaging data for two separate benchmarks: for Diabetic Retinopathy and for Prostate Cancer. For prostate cancer , the I2CVB provides a multi-parametric MRI dataset to help at the development of computer-aided detection and diagnosis (CAD) system. For each modality, a set of ground-truth is provided. The ground-truth is composed of four different classes: (i) prostate gland, (ii) peripheral zone (PZ), (iii) central gland (CG), (iv) CaP.

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Publications

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Computer-Aided Detection and diagnosis for prostate cancer based on mono and multi-parametric MRI: a review
PMID: 25747341

metasource: BiŌkeanós-Medsourcing
version: 0.0.1:2022-11-04T13:34:25.975929

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Classification of SD-OCT volumes with multi pyramids, LBP and HOG descriptors: application to DME detections
PMID: 28268574

metasource: BiŌkeanós-Medsourcing
version: 0.0.1:2022-11-04T13:34:25.975929

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• Computer-Aided Detection and diagnosis for prostate cancer based on mono and multi-parametric MRI: a review PubMed citations: 40.

  40 articles citing: Computer-Aided Detection and diagnosis for prostate cancer based on mono and multi-parametric MRI: a review

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  Multiple analyses suggests texture features can indicate the presence of tumor in the prostate tissue. PMID:35325377

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  Detection of ISUP ≥2 prostate cancers using multiparametric MRI: prospective multicentre assessment of the non-inferiority of an artificial intelligence system as compared to the PI-RADS V.2.1 score (CHANGE study). PMID:35140147

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  MRI Based Radiomics Compared With the PI-RADS V2.1 in the Prediction of Clinically Significant Prostate Cancer: Biparametric vs Multiparametric MRI. PMID:35127499

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  Magnetic Resonance Imaging Sequence Identification Using a Metadata Learning Approach. PMID:34867254

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  Automatic Segmentation of Pelvic Cancers Using Deep Learning: State-of-the-Art Approaches and Challenges. PMID:34829310

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  Multiparametric MRI and Radiomics in Prostate Cancer: A Review of the Current Literature. PMID:34679527

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  The Reproducibility of Deep Learning-Based Segmentation of the Prostate Gland and Zones on T2-Weighted MR Images. PMID:34574031

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  Artificial Intelligence Based Algorithms for Prostate Cancer Classification and Detection on Magnetic Resonance Imaging: A Narrative Review. PMID:34073627

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  Impact of neoadjuvant androgen deprivation therapy on magnetic resonance imaging features in prostate cancer before radiotherapy. PMID:33898790

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  Diagnostic accuracy of different computer-aided diagnostic systems for prostate cancer based on magnetic resonance imaging: A systematic review with diagnostic meta-analysis. PMID:33545946

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  Radiomics for Gleason Score Detection through Deep Learning. PMID:32967291

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  A Quality Control System for Automated Prostate Segmentation on T2-Weighted MRI. PMID:32961895

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  Computer-Aided Diagnosis in Multiparametric MRI of the Prostate: An Open-Access Online Tool for Lesion Classification with High Accuracy. PMID:32825612

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  Voxel-based supervised machine learning of peripheral zone prostate cancer using noncontrast multiparametric MRI. PMID:32770600

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  Progress towards Patient-Specific, Spatially-Continuous Radiobiological Dose Prescription and Planning in Prostate Cancer IMRT: An Overview. PMID:32244821

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  Factors Influencing Variability in the Performance of Multiparametric Magnetic Resonance Imaging in Detecting Clinically Significant Prostate Cancer: A Systematic Literature Review. PMID:32192942

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  Radiomics Driven Diffusion Weighted Imaging Sensing Strategies for Zone-Level Prostate Cancer Sensing. PMID:32164378

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  Detection of Dominant Intra-prostatic Lesions in Patients With Prostate Cancer Using an Artificial Neural Network and MR Multi-modal Radiomics Analysis. PMID:31850209

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  Semi-automatic classification of prostate cancer on multi-parametric MR imaging using a multi-channel 3D convolutional neural network. PMID:31468158

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  Radiomics and machine learning of multisequence multiparametric prostate MRI: Towards improved non-invasive prostate cancer characterization. PMID:31283771

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  Multisite evaluation of radiomic feature reproducibility and discriminability for identifying peripheral zone prostate tumors on MRI. PMID:31259199

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  Noninvasive Evaluation of the Pathologic Grade of Hepatocellular Carcinoma Using MCF-3DCNN: A Pilot Study. PMID:31183380

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  The current role of prostate multiparametric magnetic resonance imaging. PMID:31061799

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  Classification of suspicious lesions on prostate multiparametric MRI using machine learning. PMID:30840719

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  Prostate zonal segmentation in 1.5T and 3T T2W MRI using a convolutional neural network. PMID:30820440

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  Comparing radiomic classifiers and classifier ensembles for detection of peripheral zone prostate tumors on T2-weighted MRI: a multi-site study. PMID:30819131

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  Computer simulations suggest that prostate enlargement due to benign prostatic hyperplasia mechanically impedes prostate cancer growth. PMID:30617074

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  A Deep Learning-Based Approach for the Detection and Localization of Prostate Cancer in T2 Magnetic Resonance Images. PMID:30506124

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  Impact of androgen deprivation therapy on apparent diffusion coefficient and T2w MRI for histogram and texture analysis with respect to focal radiotherapy of prostate cancer. PMID:30478670

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  A collaborative computer aided diagnosis (C-CAD) system with eye-tracking, sparse attentional model, and deep learning. PMID:30399507

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  Detection of prostate cancer with multiparametric MRI utilizing the anatomic structure of the prostate. PMID:29923345

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  Radiomic features from pretreatment biparametric MRI predict prostate cancer biochemical recurrence: Preliminary findings. PMID:29734484

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  Computer-aided diagnosis of prostate cancer with MRI. PMID:29732440

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  Deep Convolutional Neural Networks Enable Discrimination of Heterogeneous Digital Pathology Images. PMID:29292031

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  HistoScanningTM to Detect and Characterize Prostate Cancer-a Review of Existing Literature. PMID:29064054

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  Multiparametric magnetic resonance imaging of the prostate with computer-aided detection: experienced observer performance study. PMID:28386721

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  Texture analysis of medical images for radiotherapy applications. PMID:27885836

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  Radiomics based targeted radiotherapy planning (Rad-TRaP): a computational framework for prostate cancer treatment planning with MRI. PMID:27829431

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  Computer aided diagnosis of prostate cancer: A texton based approach. PMID:27782724

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  A Novel Unsupervised Segmentation Approach Quantifies Tumor Tissue Populations Using Multiparametric MRI: First Results with Histological Validation. PMID:27734253
• Classification of SD-OCT volumes with multi pyramids, LBP and HOG descriptors: application to DME detections PubMed citations: 1.

  1 articles citing: Classification of SD-OCT volumes with multi pyramids, LBP and HOG descriptors: application to DME detections

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  Fully automated detection of retinal disorders by image-based deep learning. PMID:30610422