Alle Papers – KI in der Krebserkennung

Computer‐aided diagnosis of breast ultrasound images using ensemble learning from convolutional neural networks

DENSE-INception U-net for medical image segmentation

Breast cancer diagnosis using GA feature selection and Rotation Forest

Changes in Breast Cancer Detection and Mammography Recall Rates After the Introduction of a Computer-Aided Detection System

Automated gland and nuclei segmentation for grading of prostate and breast cancer histopathology

Breast mass segmentation in ultrasound with selective kernel U-Net convolutional neural network

Ultrasound as the Primary Screening Test for Breast Cancer: Analysis From ACRIN 6666

Computer-aided Diagnosis: How to Move from the Laboratory to the Clinic

Histopathologic Technic and Practical Histochemistry

Breast cancer detection using artificial intelligence techniques: A systematic literature review

Anniversary Paper: History and status of CAD and quantitative image analysis: The role of<i>Medical Physics</i>and AAPM

Artificial intelligence in medical imaging: switching from radiographic pathological data to clinically meaningful endpoints

Mitosis detection in breast cancer histological images An ICPR 2012 contest

Receiver-operating characteristic curve analysis in diagnostic, prognostic and predictive biomarker research

Computer Vision and Image Processing: A Practical Approach Using CVIPTools

Skin Lesion Segmentation in Dermoscopic Images With Ensemble Deep Learning Methods

Multimodal skin lesion classification using deep learning

ConvUNeXt: An efficient convolution neural network for medical image segmentation

Comparison of Full-Field Digital Mammography with Screen-Film Mammography for Cancer Detection: Results of 4,945 Paired Examinations

Identification of COVID-19 samples from chest X-Ray images using deep learning: A comparison of transfer learning approaches

Joint Classification and Regression via Deep Multi-Task Multi-Channel Learning for Alzheimer's Disease Diagnosis

Automatic Segmentation of Liver Tumor in CT Images with Deep Convolutional Neural Networks

Cervical cancer classification using convolutional neural networks and extreme learning machines

Predicting Survival After Hepatocellular Carcinoma Resection Using Deep Learning on Histological Slides

A deep feature based framework for breast masses classification