Alle Papers – KI in der Krebserkennung

Automatic breast ultrasound image segmentation: A survey

Breast Cancer Classification from Ultrasound Images Using Probability-Based Optimal Deep Learning Feature Fusion

Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support

Deep learning outperformed 11 pathologists in the classification of histopathological melanoma images

Denoising diffusion probabilistic models for 3D medical image generation

Visual grading characteristics (VGC) analysis: a non-parametric rank-invariant statistical method for image quality evaluation

Deep learning in mammography and breast histology, an overview and future trends

Human-interpretable image features derived from densely mapped cancer pathology slides predict diverse molecular phenotypes

Artificial intelligence in breast imaging

A review of image analysis and machine learning techniques for automated cervical cancer screening from pap-smear images

Deep Learning Framework for Alzheimer’s Disease Diagnosis via 3D-CNN and FSBi-LSTM

The Cardiac Atlas Project—an imaging database for computational modeling and statistical atlases of the heart

Deep convolutional neural network VGG-16 model for differential diagnosing of papillary thyroid carcinomas in cytological images: a pilot study

nucleAIzer: A Parameter-free Deep Learning Framework for Nucleus Segmentation Using Image Style Transfer

Deep ROC Analysis and AUC as Balanced Average Accuracy, for Improved Classifier Selection, Audit and Explanation

Pulmonary nodule classification with deep residual networks

Invasive cervical cancer after conservative therapy for cervical intraepithelial neoplasia

Computer-aided diagnosis of breast cancer based on fine needle biopsy microscopic images

Deep CNNs for microscopic image classification by exploiting transfer learning and feature concatenation

Radiomics-based Prognosis Analysis for Non-Small Cell Lung Cancer

Multiple Resolution Residually Connected Feature Streams for Automatic Lung Tumor Segmentation From CT Images

Radiomic versus Convolutional Neural Networks Analysis for Classification of Contrast-enhancing Lesions at Multiparametric Breast MRI

Diagnosis and detection of infected tissue of COVID-19 patients based on lung x-ray image using convolutional neural network approaches

Computational pathology: Challenges and promises for tissue analysis

Magnetic resonance imaging radiomics predicts preoperative axillary lymph node metastasis to support surgical decisions and is associated with tumor microenvironment in invasive breast cancer: A machine learning, multicenter study