Waidah Ismail

Region of adaptive threshold segmentation between mean, median and otsu threshold for dental age assessment

Adaptive threshold works at pixel level and the result of the adaptive threshold is either background or foreground. The adaptive threshold produces superior result compared to global threshold, especially for the images that have uneven pixel intensity distribution. In the dental age assessment, X-ray image is used as an aid to estimate the age of the person. The existing process of assessment is done manually. However, this can be made automatically. The process of automated dental age assessment, require threshold segmentation to separate the background and the teeth area. In order to optimize the result of the adaptive threshold, it depends on the threshold value. In this paper, we present three methods (i.e. mean, median and OTSU) to estimate the range of the threshold value. The result of the study shown that the median threshold provides better results than the mean and OTSU thresholds. In terms of the region of the segmentation, median threshold value covers more teeth followed by mean threshold and OTSU threshold. The region of segmentation is important because one of the requirements in Demirjian method is to assess all the teeth types in quadrant 2 and quadrant 3.Based on the result of the experiment shown the region of median threshold able to segment most of the teeth area in quadrant 2 and quadrant 3.

Sobel and Canny Edges Segmentations for the Dental Age Assessment

The x-ray image is a grey scale image and the distribution of the intensity of the pixel is uneven. The x-ray image widely use in dental age assessment especially Demirjian method. The purpose of the dental age assessment is to estimate the age of unidentified bodies. The current process is done manually by the examiner. The process potentially converted to an automated system. The development an automated dental age assessment required segmentation process, which is dividing the image into multiple meaningful parts based on region and edge. The edge segmentation form a contour based on the links detected. The authors present two types of edge segmentation methods (i.e. Sobel and Canny). The objective of the study is to make a comparison between the two methods. Result showed Sobel method was able to segment all the teeth area and remove the noise on the x-ray image while Canny algorithm was not able to segment all the teeth area especially incisors. The region of segmentation is important because one of the requirements in Demirjian method is to assess all the teeth types in quadrant 2 and quadrant 3. Based on the result, the experiment showed the Sobel algorithm able to segment most of the teeth area in quadrant 2 and quadrant 3.

Automatic segmentation of jaw from panoramic dental X-ray images using GVF snakes

Panoramic radiographs or dental X-rays are still a prominent tool used by the dentists for dental diagnosis. Accurate segmentation and reconstruction of each tooth from panoramic radiographs can play very significant role in early diagnosis and treatment that helps physicians to make a better decision. Panoramic radiographs contain regions outside of the jaw, which make segmentation of teeth very time consuming and complex. Automatic segmentation of jaw is necessary to avoid such complexity and to reduce time. Due to the absence of substantial difference of pixel intensity between different structures and absence of strong edges in panoramic radiographs, segmentation of jaw is still perplexing. In this paper, we use the gradient information to segment the jaw regardless of the position and size of the jaw. Our algorithm for segmentation of jaw has four steps: k-means clustering, detection of points around the jaw (proposed), gradient vector flow (GVF) snakes and correction by making the shape of the segmented area oval. K-means clustering followed by thresholding and detection of points around the jaw (proposed) is used to find suitable points for initialization of the GVF snakes. Then, GVF snakes are initialized with the detected points to segment the jaw. Finally, correction is performed by making the shape of the segmented area oval.

An automated method for the nuclei and cytoplasm of Acute Myeloid Leukemia detection in blood smear images

Leukemia is a cancer of white blood cells that affect the blood forming cells in the body. Acute Myeloid Leukemia (AML) is a form of leukemia and are caused by replacement of normal bone marrows with leukemic cells, which cause a drop in red blood cells, platelets, and normal white blood cells. Early classification of the subtype of AML cells is necessary for proper treatment management. We classify the subtype based on the features of AML cells, which include the nuclei and cytoplasm. In this paper, we developed an automate method for the nuclei and cytoplasm detection from the blood cells images that are captured as microscope images. In contrast to other methods that focus on identifying the nuclei, we proposed a method based on the color conversion, intensity threshold and gradient magnitude. Our method detected both the nuclei and the cytoplasm at the same time. We test our method on 301 images, which contain 643 AML cells. The accuracy of both nuclei and cytoplasm detection is over 82.9% (increase 17% when was compared with the existent method).

A classification on brain wave patterns for Parkinson’s patients using WEKA

In this paper, classification of brain wave using real-world data from Parkinson’s patients in producing an emotional model is presented. Electroencephalograph (EEG) signal is recorded on eleven Parkinson’s patients. This paper aims to find the “best” classification for brain wave patterns in patients with Parkinson’s disease. This work performed is based on the four phases, which are first phase is raw data and after data processing using statistical features such as mean and standard deviation. The second phase is the sum of hertz, the third is the sum of hertz divided by the number of hertz, and last is the sum of hertz divided by total hertz. We are using five attributes that are patients, class, domain, location, and hertz. The data were classified using WEKA. The results showed that BayesNet gave a consistent result for all the phases from multilayer perceptron and K-Means. However, K-Mean gave the highest result in the first phase. Our results are based on a real-world data from Parkinson’s patients.

Geometric feature descriptor and dissimilarity-based registration of remotely sensed imagery

Image registration of remotely sensed imagery is challenging, as complex deformations are common. Different deformations, such as affine and homogenous transformation, combined with multimodal data capturing can emerge in the data acquisition process. These effects, when combined, tend to compromise the performance of the currently available registration methods. A new image transform, known as geometric mean projection transform, is introduced in this work. As it is deformation invariant, it can be employed as a feature descriptor, whereby it analyzes the functions of all vertical and horizontal signals in local areas of the image. Moreover, an invariant feature correspondence method is proposed as a point matching algorithm, which incorporates new descriptor’s dissimilarity metric. Considering the image as a signal, the proposed approach utilizes a square Eigenvector correlation (SEC) based on the Eigenvector properties. In our experiments on standard test images sourced from “Featurespace” and “IKONOS” datasets, the proposed method achieved higher average accuracy relative to that obtained from other state of the art image registration techniques. The accuracy of the proposed method was assessed using six standard evaluation metrics. Furthermore, statistical analyses, including t-test and Friedman test, demonstrate that the method developed as a part of this study is superior to the existing methods.

Exploring Barriers that Affect Telerehabilitation Readiness: A Case Study of Rehabilitation Centre in Malaysia

TeleRehab enables the rehabilitation services to be delivered in distance by providing information exchange between patient with disabilities and the clinical professionals. The readiness step in any adoption of healthcare services should always be one of the requirements for a successful implementation of an innovation. However, little scholarly has been undertaken to study its influence on TeleRehab and the various barrier factors that influence its adoption. This research explores the barrier factors that influence the readiness of healthcare institution to adopt TeleRehab. This paper presents a semi-structured interview involving 23 clinical professionals of a case study on the issues of TeleRehab readiness in one rehabilitation centre in Malaysia. By applying thematic analysis, the study uncovers seven barriers that affect the TeleRehab readiness. This includes barriers of no urgency to change, less awareness, less involvement in planning, not enough exposure on e-Healthcare knowledge, resistance to change, low usage of hardware and software, and less connectivity. The study contributes to both TeleRehab management and technology readiness research in hospitals.

Organization's perspective of managing B2C e-Commerce implementation: Lessons from fashion and apparel business in Malaysia

This paper proposes an organizations perspective of the business-to-customer (B2C) e-Commerce system implementation framework in Malaysian fashion and apparel business. The framework was developed based upon two in-depth case studies which were conducted in two fashion and apparel business in Malaysia. From the cross-cases, ten implementation factors (with its characteristics) that pertinent to the stages of Kotters model have emerged. This includes factors of financial structure, e-Commerce compatibility, marketing strategy, customer analysis, e-Commerce relative advantages, rewards, e-Commerce maintenance, employee training, and e-Commerce re-engineering. Additionally, three implementation actors - e-Commerce champion, system moderator and vendor, involved in the respective stages of the implementation process. Finding of this study suggests that all the ten factors and the three implementation actors are the ingredients that organizations should not be overlooked when B2C e-Commerce implementation initiative is considered.

Virtual reality rehabilitation for stroke patients: Recent review and research issues

Stroke is one of the main causes of disability in the world. In order for stroke survivors to reduce their disability, they need to go through a rehabilitation process to regain back their independence and improve their quality of life. To guide patients in their rehabilitation process and improve their receptiveness in performing repetitive exercises, a new rehabilitation training program using Virtual Reality (VR) technology has been introduced. This has attracted many researchers to explore more on VR technology as a new tool for stroke patient’s rehabilitation. This paper presents a review on existing VR systems that have been developed for stroke rehabilitation. First, recent VR systems utilized for rehabilitation after stroke are delineated and categorized. Each of these categories concludes with a discussion on limitations and any issues that arise from it. Finally, a concise summary with significant findings and future possibilities in VR rehabilitation research is presented in table format.

Embedding organizational culture values towards successful business continuity management (BCM) implementation

Todays increased reliance on Information and Communications Technology (ICT) has raised the expectations for service quality, reliability and availability. Such expectations have introduced BCM as a crucial requirement for organizations. BCM is a management process that helps in improving the organizations resilience to interruptions caused by information security threats. The implementation of BCM not only involves the information technology (IT) department, but also business areas that use IT services. BCM however, only receives attention with the support and direction from top management whenever it is required for regulatory compliance. Therefore this paper aims to explore and identify the effects of organizational culture on the successful implementation of BCM in Malaysian organizations. Quantitative surveys have been distributed to 300 participants with varying roles within the organizational hierarchy. 22 Malaysian IT organizations and departments have been selected to participate in the survey. The survey explores the organization employees view on the importance and effect of organizational culture on BCM implementation. The results indicate that cultural factors greatly impact and play an important role to the organization in terms of BCM readiness and implementation. The results are useful as a guidance for organizations in Malaysia specifically to monitor security incidents or threats which may arise not only from technicalities but also human complexity. The results may also aid in the preparation of organizational guidelines regarding readiness towards BCM implementation.