Alle Papers – KI in der Krebserkennung

A survey on deep learning in medical image analysis

pROC: an open-source package for R and S+ to analyze and compare ROC curves

Dermatologist-level classification of skin cancer with deep neural networks

A survey on Image Data Augmentation for Deep Learning

QuPath: Open source software for digital pathology image analysis

Radiomics: Images Are More than Pictures, They Are Data

Unified segmentation

A method of comparing the areas under receiver operating characteristic curves derived from the same cases.

The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)

Radiomics: Extracting more information from medical images using advanced feature analysis

Supervised Risk Predictor of Breast Cancer Based on Intrinsic Subtypes

Deep Learning in Medical Image Analysis

Convolutional neural networks: an overview and application in radiology

Convolutional networks for images, speech, and time series

Medical image analysis: progress over two decades and the challenges ahead

The Image Biomarker Standardization Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based Phenotyping

Artificial intelligence in radiology

ilastik: interactive machine learning for (bio)image analysis

How To Build and Interpret a Nomogram for Cancer Prognosis

Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer

Machine learning applications in cancer prognosis and prediction

Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning?

beta-VAE: Learning Basic Visual Concepts with a Constrained Variational Framework

International evaluation of an AI system for breast cancer screening

The HAM10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions