Alle Papers – KI in der Krebserkennung

DICOM Format and Protocol Standardization—A Core Requirement for Digital Pathology Success

Anti-Interference From Noisy Labels: Mean-Teacher-Assisted Confident Learning for Medical Image Segmentation

Artificial intelligence in cancer diagnosis: Opportunities and challenges

Efforts to improve interobserver agreement in histopathological grading

Automatic classification of mammography reports by BI-RADS breast tissue composition class

A method to evaluate intra-operative gamma probes for sentinel lymph node localisation

Bone cancer detection using machine learning techniques

HWDCNN: Multi-class recognition in breast histopathology with Haar wavelet decomposed image based convolution neural network

Borderline Breast Lesions

Navigated Breast Tumor Excision Using Electromagnetically Tracked Ultrasound and Surgical Instruments

Age-related changes in human sublingual glands: a post mortem study

Further Applications of Archimedesʼ Principle in the Correction of Asymmetrical Breasts

Automatic thresholding of infected blood images using granulometry and regional extrema

Stain-Transforming Cycle-Consistent Generative Adversarial Networks for Improved Segmentation of Renal Histopathology

INCIDENCE AND REPORTING OF CUTANEOUS MELANOMA IN QUEENSLAND

Domain-Specific Image Analysis for Cervical Neoplasia Detection Based on Conditional Random Fields

Lightscanning versus mammography for the detection of breast cancer in screening and clinical practice. A Swedish multicenter study

Medical image registration using unsupervised deep neural network: A scoping literature review

Imaging With Synthesized 2D Mammography: Differences, Advantages, and Pitfalls Compared With Digital Mammography

Task-Specific Fine-Tuning via Variational Information Bottleneck for Weakly-Supervised Pathology Whole Slide Image Classification

Breast Cancer: Computer-aided Detection with Digital Breast Tomosynthesis

Addressing Potential Health Disparities in the Adoption of Advanced Breast Imaging Technologies

Cervical Cancer Diagnosis Using Very Deep Networks Over Different Activation Functions

Pixel-to-Pixel Learning With Weak Supervision for Single-Stage Nucleus Recognition in Ki67 Images

Facetto: Combining Unsupervised and Supervised Learning for Hierarchical Phenotype Analysis in Multi-Channel Image Data