Computer Aided Diagnosis for Screening the Shape and Size of Leukocyte Cell Nucleus based on Morphological Image

Hematology tests are examinations that aim to know the state of blood and its components, one of which is leukocytes. Hematologic examinations such as the number and morphology of blood generally still done manually, especially by a specialist pathologist. Despite the fact that today there is equipment that can identify morphological automatically, but for developing countries like Indonesia, it can only be done in the capital city. Low accuracy due to the differences identified either by doctors or laboratory staff, makes a great reason to use computer assistance, especially with the rapid technological developments at this time. In this paper, we will emphasize our experiment to screen leucocyte cell nucleus by identifying the contours of the cell nucleus, diameter, circumference and area of these cells based on digital image processing techniques, especially using the morphological image. The results obtained are promising for further development in the development of computer-aided diagnosis for identification of leukocytes based on a simple and inexpensive equipment

Brightness and Contrast Modification in Ultrasonography Images Using Edge Detection Results

Currently, ultrasonography device become an important equipment for supporting diagnosis in diesases. Unfortunetaly, a lot of ultrasonography images do not provide enough information for supporting diagnosis especially images produced by low-resolution ultrasonography. It is caused by image quality that has been produced is inadequate because of noise. This research aims to improve image quality by modifying brightness and contrast to the edge detection algorithms. By modifying the brightness and contrast will cause the value of standard deviation of the ultrasonography image is lowered. Raising setting values will cause deviation standard value becomes smaller, and also the result of standard deviation is inversely proportional to the value of RMSE.  The results show that this modification can improve image quality by reducing noise significantly

Point Processing Method for Improving Dental Radiology Image Quality

Radiology field is very important in today's world, especially in the field of medicine including dentistry. Radiology equipment that is popular in dentistry is the panoramic machine. A panoramic image facilitate the dentist in making a diagnosis of the abnormality in the mouth and teeth. But unfortunately, for developing countries like Indonesia, panoramic machine available are low resolution which have an effect on the resulting image also has low quality. This research aims to improve the quality of the panoramic image to have a better quality. We use point processing method with emphasis on contrast stretching method. We chose this method because it is quite simple but has a high performance. Based on the second opinion from the hospital, the performance is 83.9%, therefore this method is promising to be implemented on the improvement of dental radiology images

Histogram Equalization for Improving Quality of Low-resolution Ultrasonography Images

The current development of digital image processing techniques have been very rapid. Application of digital image processing both hardware and software are available with a variety of features as a form of superiority. Medical ultrasonography is one of the results of digital image processing technology. It is a kind of diagnostic imaging technique with ultrasonic that is used to produce images of internal organs and muscles, size, structure, and wound pathology, which makes this technique is useful for checking organ. However the images produced by low resolution ultrasonography device is not fully produce clear information. In this research we use histogram equalization to improve image quality. In this paper we emphasize on the comparison of the two methods in the histogram equalization, namely Enhance Contrast Using Histogram Equalization (ECHE) and Contrast-Limited Adaptive Histogram Equalization (CLAHE). The results showed that CLAHE give the best results, with the parameter value Nbins 256 and Distribution Rayleigh with MSE value 9744.80 and PSNR value 8.284150