Alle Papers – KI in der Krebserkennung

Development of a quantitative method for analysis of breast density based on three‐dimensional breast MRI

Low energy mammogram obtained in contrast-enhanced digital mammography (CEDM) is comparable to routine full-field digital mammography (FFDM)

An unsupervised learning method with a clustering approach for tumor identification and tissue segmentation in magnetic resonance brain images

NucleiSegNet: Robust deep learning architecture for the nuclei segmentation of liver cancer histopathology images

CODA: quantitative 3D reconstruction of large tissues at cellular resolution

Computer-Aided Diagnosis of Skin Diseases Using Deep Neural Networks

A review of deep learning-based information fusion techniques for multimodal medical image classification

Cervical tissue shrinkage by formaldehyde fixation, paraffin wax embedding, section cutting and mounting

Kidney disease detection and segmentation using artificial neural network and multi-kernel k-means clustering for ultrasound images

Artificial intelligence and machine learning in precision medicine: A paradigm shift in big data analysis

Artificial intelligence in cancer therapy

Benchmarking weakly-supervised deep learning pipelines for whole slide classification in computational pathology

Convolutional neural networks for computer-aided detection or diagnosis in medical image analysis: An overview

Classification of breast cancer histopathological images using interleaved DenseNet with SENet (IDSNet)

Explainable AI in medical imaging: An overview for clinical practitioners – Beyond saliency-based XAI approaches

Re-definition of claudin-low as a breast cancer phenotype

Vessel tree reconstruction in thoracic CT scans with application to nodule detection

Computer-aided breast cancer detection and diagnosis of masses using difference of Gaussians and derivative-based feature saliency

Automated Storage and Retrieval of Thin-Section CT Images to Assist Diagnosis: System Description and Preliminary Assessment

Effectiveness of Computer-Aided Detection in Community Mammography Practice

COVID-CXNet: Detecting COVID-19 in frontal chest X-ray images using deep learning

Invited Talk: U-Net Convolutional Networks for Biomedical Image Segmentation

3D Segmentation in the Clinic: A Grand Challenge II: MS lesion segmentation

An improved strategy for skin lesion detection and classification using uniform segmentation and feature selection based approach

Brain Tumor Classification Using Deep Neural Network and Transfer Learning