Preparation of 2D sequences of corneal images for 3D model building

被引:11
作者
Elbita, Abdulhakim [1 ,2 ]
Qahwaji, Rami [1 ]
Ipson, Stanley [1 ]
Sharif, Mhd Saeed [1 ]
Ghanchi, Faruque [3 ]
机构
[1] Univ Bradford, Ctr Visual Comp, Bradford BD7 1DP, W Yorkshire, England
[2] Univ Misurata, Fac Informat Technol, Misurata, Libya
[3] Bradford Teaching Hosp NHS Fdn Trust, Unit Ophthamol, Bradford, W Yorkshire, England
关键词
Artificial neural networks; Confocal microscopy; Classification; Registration; Segmentation; Z-ring adapter; CONFOCAL MICROSCOPY; NEURAL-NETWORKS; CLASSIFICATION; SEGMENTATION; RECOGNITION; TEXTURE;
D O I
10.1016/j.cmpb.2014.01.009
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
A confocal microscope provides a sequence of images, at incremental depths, of the various corneal layers and structures. From these, medical practioners can extract clinical information on the state of health of the patient's cornea. In this work we are addressing problems associated with capturing and processing these images including blurring, non-uniform illumination and noise, as well as the displacement of images laterally and in the anterior-posterior direction caused by subject movement. The latter may cause some of the captured images to be out of sequence in terms of depth. In this paper we introduce automated algorithms for classification, reordering, registration and segmentation to solve these problems. The successful implementation of these algorithms could open the door for another interesting development, which is the 3D modelling of these sequences. (C) 2014 Elsevier Ireland Ltd. All rights reserved.
引用
收藏
页码:194 / 205
页数:12
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