Agus Zainal Arifin

Image segmentation by histogram thresholding using hierarchical cluster analysis

This paper proposes a new method of image thresholding by using cluster organization from the histogram of an image. A new similarity measure proposed is based on inter-class variance of the clusters to be merged and the intra-class variance of the new merged cluster. Experiments on practical images illustrate the effectiveness of the new method.

Computer-aided system for measuring the mandibular cortical width on dental panoramic radiographs in identifying postmenopausal women with low bone mineral density

IntroductionMandibular inferior cortical width manually measured on dental panoramic radiographs may be useful for identifying postmenopausal women with low skeletal bone mineral density (BMD). Automatic measurement of cortical width may enable us to identify a large number of postmenopausal women with suspected low skeletal BMD. The purposes of this study were to develop a computer-aided system for measuring mandibular cortical width on dental panoramic radiographs and clarify the diagnostic efficacy of this system.MethodsPanoramic radiographs of 100 postmenopausal women who had had BMD assessments of the lumbar spine and the femoral neck were used in this study. Experienced oral radiologist determined the position of the mental foramen on 100 digitized dental panoramic radiographs. After determination of the mental foramen, mandibular cortical width below the mental foramen was measured automatically with a computer-aided system by identifying the area of interest, enhancing the original image, determining inner and outer margins of the cortex, and selecting an appropriate point. Cortical width measured by this system was compared with BMD of the lumbar spine and the femoral neck.ResultsThere were statistically significant correlation between cortical width measured by the computer-aided system and spinal BMD (r=0.50) and femoral neck BMD (r=0.54). These correlations were similar with those between cortical width by manual measurement and skeletal BMD. Sensitivity and specificity for identifying postmenopausal women with low spinal BMD by the computer-aided system were about 88.0% and about 58.7%, respectively. Those for identifying postmenopausal women with low femoral neck BMD by this system were about 87.5% and about 56.3%, respectively.ConclusionOur results suggest that our computer-aided system may be useful for identifying postmenopausal women with low skeletal BMD.

Computer-aided system for measuring the mandibular cortical width on panoramic radiographs in osteoporosis diagnosis

Osteoporotic fractures are associated with substantial morbidity, increased medical cost and high mortality risk. Several equipments of bone assessment have been developed to identify individuals, especially postmenopausal women, with high risk of osteoporotic fracture; however, a large segment of women with low skeletal bone mineral density (BMD), namely women with high risk of osteoporotic fractures, cannot be identified sufficiently because osteoporosis is asymptomatic. Recent studies have been demonstrating that mandibular inferior cortical width manually measured on panoramic radiographs may be useful for the identification of women with low BMD. Automatic measurement of cortical width may enable us to identify a large number of asymptomatic women with low BMD. The purpose of this study was to develop a computer-aided system for measuring the mandibular cortical width on panoramic radiographs. Initially, oral radiologists determined the region of interest based on the position of mental foramen. Some enhancing image techniques were applied so as to measure the cortical width at the best point. Panoramic radiographs of 100 women who had BMD assessments of the lumbar spine and femoral neck were used to confirm the efficacy of our new system. Cortical width measured with our system was compared with skeletal BMD. There were significant correlation between cortical width measured with our system and skeletal BMD. These correlations were similar with those between cortical width manually measured by the dentist and skeletal BMD. Our results suggest that our new system may be useful for mass screening of osteoporosis.

Image thresholding using ultrafuzziness optimization based on type II fuzzy sets

Image thresholding is a critical process in digital image processing application. However, there are some disturbing factors like image vagueness and bad illumination resulting in not satisfied image thresholding output. Several fuzzy thresholding techniques are developed to remove graylevel ambiguity during threshold selection. One of the techniques is thresholding method using type II fuzzy sets. In this paper, we propose relaxation of the ultrafuzziness measurement by considering ultrafuzziness for background and object fuzzy sets separately. The proposed method optimizing ultrafuzziness to decrease uncertainty in fuzzy system used type II fuzzy sets. Experimental results on several images show the effectiveness of the proposed method.

Non-uniform decimation-free directional filter bank using histogram analysis for image enhancement

Directional Filter Banks (DFB) is a method for directional decomposition. It has been used in image enhancement procedure that involved image with many edges. The design of Decimation-Free Directional Filter Bank (DDFB) is made to give a better result for enhancement. However, the design cannot give an adaptive directional decomposition based on input image. In this paper, we proposed a Non-Uniform Decimation-Free Directional Filter Bank (NUDDFB) using Histogram Analysis for Image Enhancement. NUDDFB can build an adaptive directional filter depends on the input image. The result shows that NUDDFB can separate each directional image better than DDFB. The use of this method in image enhancement helps to retain the image from over enhancement.

Enhancement of low quality thick blood smear microscopic images of malaria patients using contrast and edge corrections

Malaria becomes one of the diseases that cause many deaths in Indonesia, particularly in Eastern Indonesia. Parasite readings in many fields of thick blood smear microscopic images become the gold standard for the diagnosis of malaria. Therefore, it requires high-quality smear image that easily readable existence of parasites. Lack of health infrastructure, especially microscopy specifications, in endemic areas affect the availability of such smear images. Images that produced under these conditions have low quality that have characteristics: blurred, the diminished true color of object, unclear boundary, and the low contrast between the object and the background. Therefore, in this study, we propose image enhancement technique to improve the readability of parasite in the low quality of thick blood smear image. The proposed method consists of two parts, namely contrast and edge corrections. Contrast correction utilizing the integration of contrast correction globally and locally respectively using Dark Stretching and Contrast Limited Adaptive Histogram Equalization (CLAHE). Meanwhile, edge correction utilizing Unsharp Masking Filtering (UMF) to improve the edge of objects in an image. The results show that the proposed method is better in the image entropy than other methods. While the value of MSE and PSNR better if range of the histogram image is short. This value means that the proposed method can produce images that contain more information than the other methods and have a good effectiveness. So the proposed method successfully improve readability parasite in the low quality of thick blood smear image.

Image thresholding based on index of fuzziness and fuzzy similarity measure

In this paper, we propose an automatic image thresholding method based on an index of fuzziness and a fuzzy similarity measure. This work aims at overcoming the limitation of the existing method which is semi-supervised. Using an index of fuzziness, two initial regions of gray levels located at the boundaries of the histogram are defined based on the fuzzy region. Then the threshold point is found by using a fuzzy similarity measure. No prior knowledge of the image is required. Experiments on practical images illustrate the effectiveness of the proposed method.

Teeth segmentation on dental panoramic radiographs using decimation-free directional filter bank thresholding and multistage adaptive thresholding

Dental utilization typically associated with tooth shape features which are extracted from dental panoramic radiograph image. However, because dental panoramic radiograph images usually have low contrast, we need a segmentation method that can work well on low contrast images and make the tooth shape is evident. In this paper, we propose a system to do teeth segmentation using Decimation-Free Directional Filter Bank Thresholding (DDFBT) and Multistage Adaptive Thresholding (MAT). The system is built with three main steps, which are formation of vertical and horizontal directional images using DDFBT, enhancement on directional images for teeth edge reinforcement and noise removal, and segmentation using MAT with Sauvola Local Thresholding. The experimental result on 40 teeth images shows that this system has a better performance than Otsu Thresholding, Sauvola Local Thresholding, and MAT with Niblack Local Thresholding with misclassification error (ME) and relative foreground area error (RAE) values are 17.0% and 9.7%.

Classification and numbering on posterior dental radiography using support vector machine with mesiodistal neck detection

Dental radiography meets challenge to classify the dents into the proper class which useful for forensic and biomedical application. This paper proposed a novel method of classification and numbering on posterior dental radiography using support vector machine (SVM) with mesiodistal neck detection. In this method we developed SVM using a nouvelle feature with mesiodistal neck teeth. This feature was used to solve the problem in the dental image which suffered with completeness of whole part of teeth (crown-root). Preprocessing for enhancements included morphological operation, contrast adaptive, and tresholding. Every tooth has been assigned according to universal dental numbering and classified as their sequence order. Our system achieved classification precision of 90 %. This approach is robust and optimal for solving the problem of dental classification.

Detection of Branching in Trabecular Bone Using Multiscale COSFIRE Filter for Osteoporosis Identification

Mandibular bone is among the bones which mineral density is reduced due to osteoporosis. Hence, dental panoramic gradiographs have become an alternative solution to identify osteoporosis. Previous study has shown that the number of branching differs between normal people and patients with osteoporosis. Another study has proposed an algorithm called COSFIRE which is able to detect branches in retinal vessel images. However, branch structures in trabecular bone differ from that in retinal vessel images. For that reason, the COSFIRE method alone is considered unable to detect such structures. In this study, we propose multiscale mechanism to detect different size of trabecular branches. Morphological structures in the trabecular bone is first enhanced using the line operator method. Then the branches are detected using COSFIRE. Experiment of the branching detection conducted to 20 images yields an accuracy of 95.25% whereas the experiment of the classification step gives the sensitivity, specificity, and accuracy of 0.95122, 0.26315, and 0.55102, respectively.