Chien-Chuan Ko

Multiresolution registration of coronary artery image sequences

Registration of coronary arterial images taken at different times is very important for obtaining better visibility of differences between sequential images. A typical image registration algorithm often employs a similarity measure to detect the differences generated from the relative motion or gray level changes between these images. Although a number of image registration approaches have been proposed to resolve the registration problem of digital angiography, they are either computationally expensive or not very robust in the application to practical images. This paper presents a feature-based sum of absolute values of difference (SAVD) using a coarse-to-fine strategy. The proposed algorithm was demonstrated to be capable to automatically registering the arterial structures in the areas of interest selected from a pair of sequential images as well as providing fractional pixel precision in registration. Compared to other existing methods, the algorithm improves the speed and the reliability of registration when a pair of coronary arterial images are acquired at the same or almost the same phase of cardiac motion.

A fully automated identification of coronary borders from the tree structure of coronary angiograms

The accurate assessment of variations in coronary arterial dimensions plays an important role in the evaluation of ischemic heart disease and the effectiveness of treatment. Although there exist a variety of edge detection algorithms in the literature, most of them are human interactive and may provide a poor estimate on coronary lesion. In this paper, we present a new method for automatic identification of arterial borders. The proposed algorithm makes use of mathematical morphology to segment blood vessels which follow a tree structure, based on a priori knowledge of coronary anatomy. Finally, an adaptive tracking strategy is applied to automatically identify 2-D arterial borders along both sides of the vessels. This is accomplished by using an edge detection model at a branching point, matched filters, and the tree structure of the coronary artery. Experimental results show that our approach not only is insensitive to the intensity variations of background and noise, but also can extract the boundary of the coronary artery accurately.

Image analysis for skeletal evaluation of carpal bones

The assessment of bone age is an important field to the pediatric radiology. It provides very important information for treatment and prediction of skeletal growth in a developing child. So far, various computerized algorithms for automatically assessing the skeletal growth have been reported. Most of these methods made attempt to analyze the phalangeal growth. The most fundamental step in these automatic measurement methods is the image segmentation that extracts bones from soft-tissue and background. These automatic segmentation methods of hand radiographs can roughly be categorized into two main approaches that are edge and region based methods. This paper presents a region-based carpal-bone segmentation approach. It is organized into four stages: contrast enhancement, moment-preserving thresholding, morphological processing, and region-growing labeling.

AUTOMATED CLASSIFICATION OF BREAST CARCINOMA CELL BASED ON IMAGE PROCESSING AND SUPPORT VECTOR MACHINE

As breast cancer is a substantial threat to the lives of women, it has become a major health issue in the world over the past 50 years, and its incidence has increased in the recent years. Early di...

The Effectiveness of TriAccess Reading System on Comprehending Nature Science Text for Students with Learning Disabilities

The major purpose of this paper was to explore the effectiveness of an individualized reading system, TriAccess, for students with learning difficulties to comprehend the nature science text. Twenty 5thand 6thgrade students with learning disabilities participated in the experiment. All the students read the articles presented with and without multiple representations on the TriAcees system. Six articles related to Endemic species in Taiwan served as experimental material. The results of the experiment indicated that the performance of reading comprehension was better when the participants read with multiple representations.

Interactive polyp biopsy based on automatic segmentation of virtual colonoscopy

We have developed a useful system to automatically segment colonic wall based on anatomical knowledge form a series of abdomen computer tomography volume dataset. It employs distance from boundary, potential field and volumetric rendering to identify the true polyps inside human colon. The proposed system also provides an interactive user interface for navigation with virtual rendering and is applied to the sub-volume of polyp candidates with 3-D shape, gray level and curvature. It can efficiently detect polyps with two-dimensional viewing images parallel to axial, sagittal and coronal in an interactive manner. With reconstruction of CT volume data, a virtual colonography system can be used to simulate the examination of fiber optical colonography. It can help the radiologists classify the polyps in clinical diagnosis.

Three-dimensional reconstruction of biliary tract from biplane projections

Over the past few years, very little has been done in the area of 3-D reconstruction of the bile duct. Since the system in use for 3-D visualization of the biliary tree is built by surgical or autopsy materials, it generally cannot be applied to clinical diagnosis. In this paper, an algorithm for three-dimensional reconstruction of the biliary tree from two mutually orthogonal is presented to provide accurate and reproducible 3-D information of the biliary tree structure. It has been proven to be useful in diagnosis prior to operation or non-surgical treatment, particularly, obstructive stones can be visualized by using a transparency technique. As experiments demonstrated, the proposed method can be used as a useful tool for the visualization of 3-D structure of biliary tree in clinical applications.

Computerized assessing the mouse proficiency through multiple indicators

This study presents a computerized assessment tool which provides multiple parameters for evaluating a subjects pointing and selecting proficiency. The Mi-CAT system could provide effect parameters, quality parameters, and visual information that serve as the multiple indicators for clinical professionals to decide whether a pointing device or a setting is proper for a client. Besides introducing the Mi-CAT system, this study also explore the effectiveness of applying Mi-CAT in identifying a proper pointing device for a 7-year-old girl. The results reported that the multiple indicators generated from Mi-CAT system would pinpoint a better device or setting for this girl.

Erratum: Different ICT Competency but Similar Pattern between Students with/without Learning Disabilities?

This paper explored if the ICT skills is different between students with/without learning disabilities across the grades. Meanwhile the current paper also explored if the structural equation modeling (SEM) is different between the students with/without learning abilities. 547 students with LD and 2298 students without LD from grade 3 to grade 9 participated in this survey. The results indicated that although the ICT skill is different between the students with/without LD, the structure of model is similar between the two groups.

Using Expert System to Assist Mouse Proficiency Assessment

This paper described how to use expert system to assist conducting mouse proficiency assessment. The expert system was based on neural network approach. The current study shows the result of analyzing cursor measurement between able-bodied and cognitive disability users. The result of evaluation indicated that this expert system may be an available solution for clinical professional to propose the suggestion for selecting suitable device or adjusting user environment conditions. The authors also provided some suggestions for the future research.