Alle Papers – KI in der Krebserkennung
168.271 Papers insgesamt · Seite 372 von 400
Medical Image Processing and Analysis
RoentGen: Vision-Language Foundation Model for Chest X-ray Generation
Not-so-supervised: A survey of semi-supervised, multi-instance, and transfer learning in medical image analysis
Unleashing the Power of Edge-Cloud Generative AI in Mobile Networks: A Survey of AIGC Services
Fine-grained histopathological image analysis via robust segmentation and large-scale retrieval
Sentinel lymph node biopsy in patients with thin melanomas
Analysis of false-negative results after US-guided 14-gauge core needle breast biopsy
Ensemble Federated Learning Approach for Diagnostics of Multi-Order Lung Cancer
A Combined Deep CNN: LSTM with a Random Forest Approach for Breast Cancer Diagnosis
Breast Nodules Computer-Aided Diagnostic System Design Using Fuzzy Cerebellar Model Neural Networks
Breast self-examination practice and its impact on breast cancer diagnosis in Alexandria, Egypt
Oncologic Imaging and Radiomics: A Walkthrough Review of Methodological Challenges
Computer Aided Abnormality Detection for Kidney on FPGA Based IoT Enabled Portable Ultrasound Imaging System
Rethinking Boundary Detection in Deep Learning Models for Medical Image Segmentation
Classification of Red Blood Cells in Sickle Cell Anemia Using Deep Convolutional Neural Network
Digital imaging in pathology – current applications and challenges
False-positive reduction in CAD mass detection using a competitive classification strategy
Spatially constrained segmentation of dermoscopy images
Sentinel Lymph Node Biopsy for Patients With Diagnostically Controversial Spitzoid Melanocytic Tumors?
Multi-Task Pre-Training of Deep Neural Networks for Digital Pathology
The adaptive computer-aided diagnosis system based on tumor sizes for the classification of breast tumors detected at screening ultrasound
COVID-19 detection in CT and CXR images using deep learning models
A new method of detecting micro-calcification clusters in mammograms using contourlet transform and non-linking simplified PCNN
Multiple Abdominal Organ Segmentation: An Atlas-Based Fuzzy Connectedness Approach
Generation of Anonymous Chest Radiographs Using Latent Diffusion Models for Training Thoracic Abnormality Classification Systems