Alle Papers – KI in der Krebserkennung

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

Classification and mutation prediction from non–small cell lung cancer histopathology images using deep learning

The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): A Completed Reference Database of Lung Nodules on CT Scans

Automated detection of COVID-19 cases using deep neural networks with X-ray images

Accurate, Large Minibatch SGD: Training ImageNet in 1 Hour

Laser Capture Microdissection

Clinical-grade computational pathology using weakly supervised deep learning on whole slide images

Mammographic Density and the Risk and Detection of Breast Cancer

H-DenseUNet: Hybrid Densely Connected UNet for Liver and Tumor Segmentation From CT Volumes

Covid-19: automatic detection from X-ray images utilizing transfer learning with convolutional neural networks

Current Methods in Medical Image Segmentation

MultiResUNet : Rethinking the U-Net architecture for multimodal biomedical image segmentation

Opportunities and obstacles for deep learning in biology and medicine

CE-Net: Context Encoder Network for 2D Medical Image Segmentation

The practical implementation of artificial intelligence technologies in medicine

Segment anything in medical images

Simultaneous Truth and Performance Level Estimation (STAPLE): An Algorithm for the Validation of Image Segmentation

Histopathological Image Analysis: A Review

Computed Tomographic Virtual Colonoscopy to Screen for Colorectal Neoplasia in Asymptomatic Adults

U-Net: deep learning for cell counting, detection, and morphometry

Deep Learning for Health Informatics

Dataset of breast ultrasound images

Diagnostic Performance of Digital versus Film Mammography for Breast-Cancer Screening

Deformable models in medical image analysis: a survey

GAN-based synthetic medical image augmentation for increased CNN performance in liver lesion classification