Computer-aided alignment method of optical lens with high accuracy

2016 ◽  
Author(s):  
Song Xing ◽  
Xiao-hua Hou ◽  
Xue-min Zhang ◽  
Bin-dong Ji
2010 ◽  
Author(s):  
Xi-ting Zhao ◽  
Wen-chun Jiao ◽  
Zhi-bo Liao ◽  
Yun Wang ◽  
Jia-yi Chen

2016 ◽  
Vol 37 (4) ◽  
pp. 607-611
Author(s):  
Yue Pengyuan ◽  
Zhao Xiting ◽  
Zhao Zhen ◽  
Wan Yuxi

1980 ◽  
Vol 27 (5) ◽  
pp. 899-906 ◽  
Author(s):  
M.H. White ◽  
F. Van De Wiele ◽  
J.-P. Lambot

2019 ◽  
Vol 12 (3) ◽  
pp. 103-110
Author(s):  
Toonlanat Thuanthong ◽  
Paiwan Sudwan

AbstractBackgroundIdentification of sex from skeletal remains is an essential step in forensic anthropology. The skull is the second choice, after the pelvis, to estimate sex by osteometric methods.ObjectiveTo evaluate the process of identification of sex in Northern Thai from crania by using computer-aided design (AutoCAD) software and conventional caliper methods.MethodsDry skulls of 86 men and 74 women were examined. AutoCAD software and digital calipers were used to measure dimensions. Eleven of the 15 parameters were created for this study.ResultsMen are significantly larger than women in all parameters, except in the nasospinale–prosthion measurement. There were no significant differences in the intraobserver error test and between the AutoCAD and digital caliper measurements. The logistic regression analysis yielded a sex classification accuracy rate of 92.9% in men, 93.4% in women, and 93.1% of overall accuracy for AutoCAD software. When using digital calipers, there was an accuracy rate of 89.3% in men, 94.7% in women, and 91.9% for overall accuracy.ConclusionsAutoCAD software is a reliable method to predict the sex and provide high accuracy in sex determination from crania.


2020 ◽  
Vol 20 (03) ◽  
pp. 2050021
Author(s):  
P. Nikesh ◽  
G. Raju

Efficient skin lesion segmentation algorithms are required for computer aided diagnosis of skin cancer. Several algorithms were proposed for skin lesion segmentation. The existing algorithms are short of achieving ideal performance. In this paper, a novel semi-automatic segmentation algorithm is proposed. The fare concept of the proposed is 8-directional search based on threshold for lesion pixel, starting from a user provided seed point. The proposed approach is tested on 200 images from PH2 and 900 images from ISBI 2016 datasets. In comparison to a chosen set of algorithms, the proposed approach gives high accuracy and specificity values. A significant advantage of the proposed method is the ability to deal with discontinuities in the lesion.


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