3D small structure detection in medical image using texture analysis

Author(s):  
Fei Gao ◽  
Min Zhang ◽  
Teresa Wu ◽  
Kevin M. Bennett
2020 ◽  
Vol 7 (4) ◽  
pp. 79-86
Author(s):  
Nagadevi Darapureddy ◽  
Nagaprakash Karatapu ◽  
Tirumala Krishna Battula

This paper examines a hybrid pattern i.e. Local derivative Vector pattern and comparasion of this pattern over other different patterns for content-based medical image retrieval. In recent years Pattern-based texture analysis has significant popularity for a variety of tasks like image recognition, image and texture classification, and object detection, etc. In literature, different patterns exist for texture analysis. This paper aims at forming a hybrid pattern compared in terms of precision, recall and F1-score with different patterns like Local Binary Pattern (LBP), Local Derivative Pattern (LDP), Completed Local Binary Pattern (CLBP), Local Tetra Pattern (LTrP), Local Vector Pattern (LVP) and Local Anisotropic Pattern (LAP) which were applied on medical images for image retrieval. The proposed method is evaluated on different modalities of medical images. The results of the proposed hybrid pattern show biased performance compared to the state-of-the-art. So this can further extended with other pattern to form a hybrid pattern.


Author(s):  
John R. Devaney

Occasionally in history, an event may occur which has a profound influence on a technology. Such an event occurred when the scanning electron microscope became commercially available to industry in the mid 60's. Semiconductors were being increasingly used in high-reliability space and military applications both because of their small volume but, also, because of their inherent reliability. However, they did fail, both early in life and sometimes in middle or old age. Why they failed and how to prevent failure or prolong “useful life” was a worry which resulted in a blossoming of sophisticated failure analysis laboratories across the country. By 1966, the ability to build small structure integrated circuits was forging well ahead of techniques available to dissect and analyze these same failures. The arrival of the scanning electron microscope gave these analysts a new insight into failure mechanisms.


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