Amanote Research
Register
Sign In
Mammographic Mass Detection With a Hierarchical Image Probability (HIP) Model
doi 10.1117/12.387603
Full Text
Open PDF
Abstract
Available in
full text
Date
June 6, 2000
Authors
Clay D. Spence
Lucas Parra
Paul Sajda
Publisher
SPIE
Related search
A New and Fast Image Feature Selection Method for Developing an Optimal Mammographic Mass Detection Scheme
Medical Physics
Medicine
Nuclear Medicine
Radiology
Imaging
Biophysics
Computing Mammographic Density From a Multiple Regression Model Constructed With Image-Acquisition Parameters From a Full-Field Digital Mammographic Unit
Physics in Medicine and Biology
Radiological
Radiology
Nuclear Medicine
Ultrasound Technology
Imaging
Automatic Application Level Set Approach in Detection Calcifications in Mammographic Image
International Journal of Computer Science and Information Technology
Image Resampling Effects in Mammographic Image Simulation
Physics in Medicine and Biology
Radiological
Radiology
Nuclear Medicine
Ultrasound Technology
Imaging
Fast Image Registration by Hierarchical Soft Correspondence Detection
Pattern Recognition
Signal Processing
Computer Vision
Pattern Recognition
Artificial Intelligence
Software
Probability of Detection Model for Pipeline Inspection
A Generalizable Hierarchical Bayesian Model for Persistent SAR Change Detection
Management Problems in Mammographic Mass Screening.
Nihon Nyugan Kenshin Gakkaishi (Journal of Japan Association of Breast Cancer Screening)
Sonar Image Segmentation Using an Unsupervised Hierarchical MRF Model
IEEE Transactions on Image Processing
Computer Graphics
Computer-Aided Design
Software