1. AM-FM texture segmentation in electron microscopic muscle imaging
- Author
-
Pattichis, Marios S., Pattichis, Constantinos S., Avraam, Maria, Bovik, Alan Conrad, Kyriacou, Kyriacos C., Pattichis, Constantinos S. [0000-0003-1271-8151], and Pattichis, Marios S. [0000-0002-1574-1827]
- Subjects
Myopathies, Nemaline ,Sarcomere ,law.invention ,Image texture ,law ,Frequency modulation ,Computer vision ,Segmentation ,Ultrasonography ,Image segmentation ,Radiological and Ultrasound Technology ,Mitochondrial Myopathies ,methodology ,Textures ,Anatomy ,Muscle imaging ,Computer Science Applications ,medicine.anatomical_structure ,Texture analysis ,Muscle ,Myopathies ,Medical imaging ,medicine.symptom ,nemaline myopathy ,myopathy ,Myopathies, Structural, Congenital ,Sarcomeres ,Muscle imagings ,Materials science ,letter ,Texture (geology) ,Amplitude modulation ,medicine ,Electron microscopy ,Humans ,human ,Electrical and Electronic Engineering ,skeletal muscle ,Myopathy ,Muscle, Skeletal ,AM/FM/GIS ,business.industry ,mitochondrial myopathy ,Skeletal muscle ,echography ,Microscopy, Electron ,Ultrastructure ,AM-FM modeling ,pathology ,sarcomere ,Artificial intelligence ,Electron microscope ,business ,Software ,Biomedical engineering - Abstract
This paper describes the application of an amplitude modulation-frequency modulation (AM-FM) image representation in segmenting electron micrographs of skeletal muscle for the recognition of: 1) normal sarcomere ultrastructural pattern and 2) abnormal regions that occur in sarcomeres in various myopathies. A total of 26 electron micrographs from different myopathies were used for this study. It is shown that the AM-FM image representation can identify normal repetitive structures and sarcomeres, with a good degree of accuracy. This system can also detect abnormalities in sarcomeres which alter the normal regular pattern, as seen in muscle pathology, with a recognition accuracy of 75%-84% as compared to a human expert. © 2000 IEEE. 19 12 1253 1258 Cited By :24
- Published
- 1999