Yan Chai Hum

Multiobjectives bihistogram equalization for image contrast enhancement

The global histogram equalization HE has been the most frequently adopted image contrast enhancement technique. A brightness and detail-preserving HE method with good contrast enhancement effect has been a goal of much recent research in HE. Nevertheless, producing a well-balanced HE is deemed to be a daunting task. In this article, we propose a novel framework of HE with the aim of taking three desirable properties into account: brightness preservation, detail preservation, and contrast enhancement. We termed the proposed method as multipurpose beta optimized bi-HE MBOBHE. MBOBHE consists of performing the histogram optimization separately in both subhistograms after the segmentation of histogram using an optimized separating point based on the three performance criteria using a weighted-sum aggregated objective function AOF. Both quantitative and qualitative results indicate that MBOBHE outperforms other existing bi-HE methods, in terms of comprehensive performance of HE that is capable of providing a holistic view.

Advances in Medical Diagnostic Technology

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Review on Segmentation of Computer-Aided Skeletal Maturity Assessment

Bone age assessment (BAA) is an examination of ossification development with the purpose of deducing the skeletal age of children to monitor their skeletal development and predict their future adult height. Conventionally, it is performed by comparing left-hand radiographs to standard atlas by visual inspection; this process is subjective and time-consuming; therefore, the automated inspection system to overcome the drawbacks is established. However, the automated BAA system invariably confronts with problem in segmentation, which is the most crucial procedure in the computer-aided BAA. Inappropriate segmentation methods will produce unwanted noises that will affect the subsequent processes of the system. The current manual or semi-automated segmentation frameworks have impeded the system from becoming truly automated, objective, and efficient. The objective of this thesis is to provide a solution to the mentioned unsolved technical problem in segmentation for automated BAA system. The task is accomplished by first applying the modified histogram equalized module, then undergoing the proposed automated anisotropic diffusion, following by a novel fuzzy quadruple division scheme to optimize the central segmentation algorithm, and finally, the process ends with an additional quality assurance scheme. The designed segmentation framework works without the need of resources such as training sets and skillful operator. The quantitative and qualitative analysis of the resultant images have both shown that the designed framework is capable of separating the soft tissue and background from the hand bone with relatively high accuracy despite omitting the above-mentioned resources.

Adaptive Network Based Fuzzy Inference System (ANFIS) for an Active Transfemoral Prosthetic Leg by Using In-Socket Sensory System

Prosthetic leg is known as one of the solutions to help the amputee to regain back their ambulation ability. However, most of the current existing knee components still lacks in the ability to provide active body propulsion, which in turn. Thus, higher metabolic energy consumption is required by the amputee in doing locomotion movement. Hence, this study proposed the idea of developing both the mechanical structure as well as an ANFIS knowledge-based control system of the active actuated knee joint for transfemoral (TF) prosthetic leg. ANFIS was adopted using Matlab software to analyze human gait phase recognition necessary for cadence and torque control required by the knee joint mechanism while the actuated knee joint was developed using Inventor CAD software. Physical simulation of the controller presented a realistic simulation of the actuated of the knee joint in terms of knee mechanism. The fuzzy system could replicate human gait cycle by categorizing the cycle into seven gait phases.

Ultrasonic Elastography and Breast Imaging

The elastography is based on the principles: (1) Tissue compression produces strain (displacement) within the tissue, and (2) this strain is lower in harder tissues than in softer tissues. Therefore, by measuring tissue strain due to compression, tissue stiffness can be estimated. Since malignant breast tissue is generally harder than normal surrounding tissue, tissue hardness observed in elastography becomes the more precise clinical information than manual palpation. The use of quantitative elastography achieves the improvement in breast cancer diagnostic accuracy.

Sequential Process of Emotional Information from Facial Expressions: Simple Event-Related Potential (ERP) for the Study of Brain Activities

Human is socially living creature that needs to communicate with others. In direct communication, there are two ways in conveying the information: through speaking words or verbally and through facial expression, body gesture or non-verbally. The non-verbal communication is taken almost 70 % of humans’ communication. Therefore, to understand how this non-verbal information is processed by the brain is quite important. In this chapter, we would like to elucidate the process of the brain in understanding the facial expression by analyzing the brain signals that correspond to emotional content of facial expression. As known, the emotion can be differentiated into the type and the level of emotion. For example, though we know that smiley face and joyful face belong to the same type of happiness, we know that the level of happiness is higher in the joyful face. Therefore, how does the brain process this kind of type and level of emotional information is the basic question that we would like to answer in this chapter. In this chapter, we explain the way we collect the data, the step-by-step process of reducing the noise in the brain signals, the way of inter-correlating the behavioral data and brain signals, how we used those data to find the location of activated brain area for processing the specific content of emotion, and finally, how we exactly find that the process of understanding the emotional information from facial expression is a sequential process; understanding the type of emotion, followed by the level of that specific emotion. This emotional process is different from that of the process of understanding the physical content of the face, like identity and gender.

A Novel Hybrid Magnetoacoustic Measurement Method for Breast Cancer Detection

Breast cancer is the most common cancer in women worldwide. It is a disease of uncontrolled breast cells growth, in which the cells acquire genetic alteration, causing them to proliferate more aggressively as compared to normal tissue development. In current medical practice, the gold standard for breast cancer screening is mammography. However, its usage is unsafe as it exposes patient to ionizing radiation and it is less comfortable due to the need for breast compression. Another available option for breast screening is ultrasound. To date, ultrasound is an important adjunct modality to mammography regardless of its low sensitivity in detecting small cancers from normal tissues due to overlapping ultrasonic characteristics of these tissues. To address this problem, a hybrid magnetoacoustic measurement method (HMM) that combines ultrasound and magnetism for the simultaneous assessment of bioelectric and acoustic profiles of breast tissue is proposed. Previous studies have shown that in cancerous tissue, changes in ultrasonic characteristics occur due to uncontrolled cell multiplication, excessive accumulation of protein in stroma, and enhancement of capillary density. Additionally, changes in conductivity also occur due to the increase in cellular water and electrolyte content, as well as membrane permeability due to increased metabolic requirements. In HMM, the interaction between the ultrasound wave and the magnetic field in the breast tissue results in Lorentz force. This produces a magnetoacoustic voltage output, which is proportional to breast tissue conductivity. Simultaneously, the ultrasound wave is sensed back by the ultrasound receiver for tissue acoustic evaluation. At the end of this study, ultrasound wave characterization results showed that normal breast tissue experienced higher attenuation compared with cancerous tissue. The mean magnetoacoustic voltage results for normal tissue were lower than the cancerous tissue group. This demonstrates that the combination of acoustic and bioelectric measurements appears to be a promising approach for diagnosis.