The objective of this Brief is to provide a solution to the unsolved technical problem in segmentation for the automated bone age assessment system. The task is accomplished by first applying the modified histogram equalized module, then applying the proposed automated anisotropic diffusion technique. It is followed by a novel fuzzy quadruple division scheme to optimize the central segmentation algorithm, and then an additional quality assurance scheme. The designed segmentation framework works without demanding scarce resources such as training sets and skillful operators. The results have shown that the designed framework is capable of separating the soft-tissue and background from the hand bone with high accuracy. This Brief should be especially useful for students and professional researchers in the Biomedical and image processing fields.

Dr. Hum Yan Chai received his PhD in the field of Biomedical Imaging from the Universiti Teknologi Malaysia (UTM). He is currently working as a researcher in the Medical Implant Technology Group (MEDITEG), Materials and Manufacturing Research Alliance. His research interests are: computerized bone age assessment, Digital X-Ray imaging, medical image processing, filter design, fuzzy logic, medical computing and performance optimization. He serves as the member of editorial board for a few international journals in relevant fields. He is also a program committee member and peer reviewer for over 15 international conferences.

Introduction.- The conventional segmentation methods.- The advanced segmentation method.- The possible solution.- Result analysis and discussion.- Conclusions and recommendations.