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An Efficient Detection and Classification of Acute Leukemia Using Transfer Learning and Orthogonal Softmax Layer-Based Model

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Fully Automatic Deep Learning Framework for Pancreatic Ductal Adenocarcinoma Detection on Computed Tomography

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Predicting the 1p/19q Codeletion Status of Presumed Low-Grade Glioma with an Externally Validated Machine Learning Algorithm

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Breast cancer cell–derived microRNA-155 suppresses tumor progression via enhancing immune cell recruitment and antitumor function

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VoCo: A Simple-Yet-Effective Volume Contrastive Learning Framework for 3D Medical Image Analysis

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CT-Based COVID-19 triage: Deep multitask learning improves joint identification and severity quantification

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Usefulness of gradient tree boosting for predicting histological subtype and EGFR mutation status of non-small cell lung cancer on 18F FDG-PET/CT

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Quality control and whole-gland, zonal and lesion annotations for the PROSTATEx challenge public dataset

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Convolutional-Neural-Network Assisted Segmentation and SVM Classification of Brain Tumor in Clinical MRI Slices

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Data infrastructures for AI in medical imaging: a report on the experiences of five EU projects

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Systematic Review of Hybrid Vision Transformer Architectures for Radiological Image Analysis

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High Bit-Depth Medical Image Compression With HEVC

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Computer-aided classification of prostate cancer grade groups from MRI images using texture features and stacked sparse autoencoder

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Noninvasive O6 Methylguanine-DNA Methyltransferase Status Prediction in Glioblastoma Multiforme Cancer Using Magnetic Resonance Imaging Radiomics Features: Univariate and Multivariate Radiogenomics Analysis

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Deep and statistical learning in biomedical imaging: State of the art in 3D MRI brain tumor segmentation

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Data synthesis and adversarial networks: A review and meta-analysis in cancer imaging

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Integration of convolutional neural networks for pulmonary nodule malignancy assessment in a lung cancer classification pipeline

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A U-Net Ensemble for breast lesion segmentation in DCE MRI

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A method of rapid quantification of patient‐specific organ doses for CT using deep‐learning‐based multi‐organ segmentation and GPU‐accelerated Monte Carlo dose computing

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