Alle Papers – KI in der Krebserkennung

A foundation model for clinical-grade computational pathology and rare cancers detection

Medical Image Computing and Computer-Assisted Intervention — MICCAI 2002

A deep learning approach to automatic teeth detection and numbering based on object detection in dental periapical films

Prediction of benign and malignant breast cancer using data mining techniques

MDNet: A Semantically and Visually Interpretable Medical Image Diagnosis Network

CT texture analysis using the filtration-histogram method: what do the measurements mean?

The Role of Artificial Intelligence in Early Cancer Diagnosis

A Survey of Deep-Learning Applications in Ultrasound: Artificial Intelligence–Powered Ultrasound for Improving Clinical Workflow

Automated deep learning design for medical image classification by health-care professionals with no coding experience: a feasibility study

SV-RCNet: Workflow Recognition From Surgical Videos Using Recurrent Convolutional Network

AAU-Net: An Adaptive Attention U-Net for Breast Lesions Segmentation in Ultrasound Images

Computer Aided Melanoma Skin Cancer Detection Using Image Processing

<title>Segmentation of medical images using adaptive region growing</title>

Two-Stage Cascaded U-Net: 1st Place Solution to BraTS Challenge 2019 Segmentation Task

U-Net-Based Medical Image Segmentation

The Virtual Skeleton Database: An Open Access Repository for Biomedical Research and Collaboration

Opportunities and obstacles for deep learning in biology and medicine

Predicting factors for survival of breast cancer patients using machine learning techniques

A Review of Dimensionality Reduction Techniques for Efficient Computation

A study on several Machine-learning methods for classification of Malignant and benign clustered microcalcifications

A radiogenomic dataset of non-small cell lung cancer

Glioma Grading on Conventional MR Images: A Deep Learning Study With Transfer Learning

Random forest classifier combined with feature selection for breast cancer diagnosis and prognostic

Deep learning techniques for skin lesion analysis and melanoma cancer detection: a survey of state-of-the-art

What the radiologist should know about artificial intelligence – an ESR white paper