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).

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.

Blood cancer is an umbrella term for cancers that affect the blood, bone marrow and lymphatic system. There are three main groups of blood cancer: leukemia, lymphoma and myeloma. Some types are more common than others. In this paper, a new image transform based on geometric mean properties of integral values in both horizontal and vertical image directions is proposed for leukemia cancer cell classification. Available classification methods using the classical feature extraction methods which are sensitive to rotation and deformation of the blood cells. The new transform is based on geometric mean projection, which - unlike other image transforms, such as Radon transform-is not considered all signals in an image with the same signal acquisition rate. Instead, it is general and thus applicable to all capturing signal functions to achieve sufficient invariant features. The geometric mean projection transforms (GMPT) guarantees that the detector only extracts the highly informative information from the object to achieve an invariant feature vector for an accurate classification process. This method has been used as cancer cell identification using microscopic Imagery analysis in this study. Dissimilarity metric calculation and shape analysis by using image transform has been used to extract the feature vectors of the imagery. Then, the accumulated feature vectors have been classified to different classes by using artificial neural network (ANN). The proposed technique has been evaluated in the standard images sourced from USIM, Malaysia. The evaluation results indicate the robustness of the technique in different types of images available in the dataset.

Every now and then, our lives are influenced by the development of technologies and this had changed the perception of business in several ways. Now the world is focusing on wireless devices that can be developed to have exchange of data either using internet or not. Near Field Communication (NFC) is one of the devices that has the capability to securely exchange data with its paired devices and Radio-Frequency Identification (RFID) is developed to broadcast a unique identifying number upon request. This paper concentrates on the security element in the NFC and RFID in the implementation of NFC technology in blood transfusion; to solve the problems of human error and to avoid from transfusing different blood types than the ones actually needed by the patient. The information in the wrist tag should be synchronized with the current hospital system. This NFC technology is also for reducing the use of paper-based documents, consequently promoting green technology. As a result, choosing the NFC or RFID based on the security features is very important for patient identification as well as moving towards green technology.

Clustering is one of the most common automated image segmentation techniques used in many fields including machine learning, pattern recognition, image processing, and bioinformatics. Recently many scientists have performed tremendous research in helping the hematologists in the issue of segmenting the blood cells in the early of prognosis. This paper aims to segment the blood cell images of patients suffering from acute leukemia using an adaptive K-Means clustering together with mean shift algorithm. The integrated clustering techniques have produced comprehensive output images with minimal filtering process to remove the background scene.

Short tandem repeat (STR) analysis is used in chimerism monitoring after allogeneic hematopoietic stem cell transplantation (HSCT) for patients with various hematologic malignancies. Commercial forensic STR kits often contain loci with huge differences in power of discrimination (PD) across populations, causing some loci to be less informative for chimerism analysis in certain populations. This study aimed to construct a new STR multiplex panel with highly informative loci for efficient chimerism analysis. Thirteen STR markers which exhibit high PD (> 0.9) in at least 80% of 50 populations globally were selected to form a new panel and used in STR analysis of 253 Malaysian subjects. Cumulative power of discrimination (CPD) and combined power of exclusion (CPE) were determined from 253 Malaysian individuals. Loci informativity was assessed and compared to the commercial AmpFLSTR Identifiler PCR Amplification kit in 14 donor-recipient pairs. The new panel had detected 202 unique alleles including five novel alleles from the 253 individuals with high CPD and CPE (> 0.99999999999999999 and > 0.999999997 respectively). All loci from the new panel in the donor-recipient pair analysis showed higher than 50% informativity, while five loci from the commercial kit demonstrated lower than 50% informativity. Four loci from the new panel ranked the highest informativity. A sequenced allelic ladder which consists of 202 unique alleles from the 253 subjects was also developed to ensure accurate allele designation. The new 13-loci STR panel, thus, could serve as an additional powerful, accurate, and highly informative panel for chimerism analysis for HSCT patients.

Cooperative sector governance is instrumental in ensuring the effectiveness, responsibility, and accountability in both conventional and Shari'ah-compliant cooperatives. This study examines Shari'ah governance (SG) arrangements within the cooperatives in Malaysia. The objectives of this paper are to explore the application of SG in the cooperative sector in Malaysia and to evaluate the adequacy of SG adoption in cooperative. This study uses qualitative methods where the data are collected using focus group discussions and in-depth interviews with regulators, experts, and the governance organs of the cooperatives. The study focuses on credit cooperatives that have been listed in the 100 Best Cooperative Directory issued by Suruhanjaya Koperasi Malaysia (SKM) annually from 2012 to 2016. The findings from thematic analysis on interviews conducted indicate that the first objective, most respondents agreed that cooperatives should be operated based on the objectives of its establishment. The findings on the adequacy of adoption of SG in Shari 'ah-compliant cooperatives indicate that the practice is at an infancy stage, with plenty of support and motivation are needed to ensure effective and efficient implementation of SG. Emergent findings from the interviews reveal that the Islamic attributes are crucial for a cooperative's SG organs such as Islamic accountability, Shari'ah mindset, Islamic culture, awareness and readiness, manpower competencies and cooperation (ta'awun). It is vital for the SG organs to have such attributes in order to foster awareness among them to be more responsible and willing to adopt good SG practices. The observation of good SG practices in the cooperative sector in Malaysia can help the cooperative movement to positively grow and contribute equitably to community.

The x-ray image is a greyscale 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.