Alle Papers – KI in der Krebserkennung

Fully-automated deep learning pipeline for segmentation and classification of breast ultrasound images

Parity and mammographic breast density in relation to breast cancer risk

Identification of Breast Malignancy by Marker-Controlled Watershed Transformation and Hybrid Feature Set for Healthcare

Multi-view Convolutional Neural Network for lung nodule false positive reduction

An automatic COVID-19 CT segmentation based on U-Net with attention mechanism

SADM: Sequence-Aware Diffusion Model for Longitudinal Medical Image Generation

Lung Cancer Classification using Optimized Attention-based Convolutional Neural Network with DenseNet-201 Transfer Learning Model on CT image

FABNet: Fusion Attention Block and Transfer Learning for Laryngeal Cancer Tumor Grading in P63 IHC Histopathology Images

Texture feature extraction based on wavelet transform and gray-level co-occurrence matrices applied to osteosarcoma diagnosis

Multi-feature gradient vector flow snakes for adaptive segmentation of the ultrasound images of breast cancer

Documenting Clinical and Laboratory Images in Publications

The Future of Telepathology for the Developing World

Euclidean distance-optimized data transformation for cluster analysis in biomedical data (EDOtrans)

Ultrasonic grey scale visualization of breast disease

Revisiting Rubik’s Cube: Self-supervised Learning with Volume-Wise Transformation for 3D Medical Image Segmentation

Automatic detection of solitary pulmonary nodules using swarm intelligence optimized neural networks on CT images

Comparison of ultrasound and mammography for early diagnosis of breast cancer among Chinese women with suspected breast lesions: A prospective trial

A deep learning algorithm for classification of oral lichen planus lesions from photographic images: A retrospective study

SAM-U: Multi-box Prompts Triggered Uncertainty Estimation for Reliable SAM in Medical Image

An explainable AI-driven biomarker discovery framework for Non-Small Cell Lung Cancer classification

A High-Performance Deep Neural Network Model for BI-RADS Classification of Screening Mammography

2D and 3D texture analysis to predict lymphovascular invasion in lung adenocarcinoma

Visually Navigated Bronchoscopy using three cycle-Consistent generative adversarial network for depth estimation

A novel image-to-knowledge inference approach for automatically diagnosing tumors

A Multi-Task Learning Framework for Automated Segmentation and Classification of Breast Tumors From Ultrasound Images