Alle Papers – KI in der Krebserkennung

Emerging Themes in Image Informatics and Molecular Analysis for Digital Pathology

Automated Detection and Forecasting of COVID-19 using Deep Learning Techniques: A Review

Deep learning for liver tumor diagnosis part II: convolutional neural network interpretation using radiologic imaging features

Determining breast cancer biomarker status and associated morphological features using deep learning

Comprehensive analysis of lung cancer pathology images to discover tumor shape and boundary features that predict survival outcome

US-guided Core-Needle Biopsy of the Breast: How Many Specimens Are Necessary?

Exploring the clinical potential of an automatic colonic polyp detection method based on the creation of energy maps

ITK-SNAP: An Intractive Medical Image Segmentation Tool to Meet the Need for Expert-Guided Segmentation of Complex Medical Images

Using deep learning for dermatologist-level detection of suspicious pigmented skin lesions from wide-field images

Dermatologist-Level Classification of Skin Cancer Using Cascaded Ensembling of Convolutional Neural Network and Handcrafted Features Based Deep Neural Network

Computerized detection of masses in digital mammograms: Automated alignment of breast images and its effect on bilateral‐subtraction technique

A sensitivity and specificity comparison of fine needle aspiration cytology and core needle biopsy in evaluation of suspicious breast lesions: A systematic review and meta-analysis

Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery

Clinicians are from Mars and pathologists are from Venus.

End-to-end prostate cancer detection in bpMRI via 3D CNNs: Effects of attention mechanisms, clinical priori and decoupled false positive reduction

Few-shot medical image segmentation using a global correlation network with discriminative embedding

Pre-validation and inference in microarrays

A practical application of neural network analysis for predicting outcome of individual breast cancer patients

AUNet: attention-guided dense-upsampling networks for breast mass segmentation in whole mammograms

Skin Lesion Segmentation from Dermoscopic Images Using Convolutional Neural Network

Clear Cell Renal Cell Carcinoma: Machine Learning-Based Quantitative Computed Tomography Texture Analysis for Prediction of Fuhrman Nuclear Grade

RUN-LENGTH ENCODING FOR VOLUMETRIC TEXTURE

Computerized scheme for automated detection of lung nodules in low-dose computed tomography images for lung cancer screening1

Characterization of clustered microcalcifications in digitized mammograms using neural networks and support vector machines

Visualization in Medicine: Theory, Algorithms, and Applications