Alle Papers – KI in der Krebserkennung

Computer-aided diagnosis system combining FCN and Bi-LSTM model for efficient breast cancer detection from histopathological images

EANM-EORTC general recommendations for sentinel node diagnostics in melanoma

Geometric Structure of High-Dimensional Data and Dimensionality Reduction

ANGY: A Rule-Based Expert System for Automatic Segmentation of Coronary Vessels From Digital Subtracted Angiograms

Automated breast cancer detection in digital mammograms: A moth flame optimization based ELM approach

Detection and classification of lung abnormalities by use of convolutional neural network (CNN) and regions with CNN features (R-CNN)

Primary frozen section diagnosis by robotic microscopy and virtual slide telepathology: the University Health Network experience

Intelligent Health Care: Applications of Deep Learning in Computational Medicine

Breast Tomosynthesis

Comparison of Seven Tests for High-Grade Cervical Intraepithelial Neoplasia in Women with Abnormal Smears: the Predictors 2 Study

Applying deep learning in digital breast tomosynthesis for automatic breast cancer detection: A review

Bridging the implementation gap of machine learning in healthcare

An identification method of malignant and benign liver tumors from ultrasonography based on GLCM texture features and fuzzy SVM

A survey on deep learning applied to medical images: from simple artificial neural networks to generative models

Rethinking the unpretentious U-net for medical ultrasound image segmentation

ConvXGB: A new deep learning model for classification problems based on CNN and XGBoost

Pixels to Classes: Intelligent Learning Framework for Multiclass Skin Lesion Localization and Classification

Image Processing Algorithms for Digital Mammography: A Pictorial Essay

Machine Learning in Detection and Classification of Leukemia Using Smear Blood Images: A Systematic Review

Learning statistical models of phenotypes using noisy labeled training data

Deep Learning for Chest Radiograph Diagnosis in the Emergency Department

Integrating Feature Selection and Feature Extraction Methods With Deep Learning to Predict Clinical Outcome of Breast Cancer

Independent real‐world application of a clinical‐grade automated prostate cancer detection system

2012 5th International Congress on Image and Signal Processing

Automated Leukaemia Detection Using Microscopic Images