다중혈관 관상동맥 환자에서 y-문합을 이용하여 양쪽 내흉동맥만을 사용한 우회술의 조기 성적

[신간의 별자리x] 우리/미술, 그리고 ‘슬픔의 박물관’

International Journal of Computer and Applications

There has been a great deal of material in the area of discrete-time transforms that has been published in recent years. This book does an excellent job of presenting important aspects of such material in a clear manner. The book has 11 chapters and a very useful appendix. Seven of these chapters are essentially devoted to the Fourier series/transform, discrete Fourier transform, fast Fourier transform (FFT), and applications of the FFT in the area of spectral estimation. Chapters 8 through 10 deal with many other discrete-time transforms and algorithms to compute them. Of these transforms, the KarhunenLoeve, the discrete cosine, and the Walsh-Hadamard transform are perhaps the most well-known. A lucid discussion of number theoretic transforms i5 presented in Chapter 11. This reviewer feels that the authors have done a fine job of compiling the pertinent material and presenting it in a concise and clear manner. There are a number of problems at the end of each chapter, an appreciable number of which are challenging. The authors have included a comprehensive set of references at the end of the book. In brief, this book is a valuable contribution to the general areas of signal processing and communications. It can be used for a graduate level course in perhaps two ways. One would be to cover the first seven chapters in great detail. The other would be to cover the whole book by focussing on different topics in a selective manner. This book  by  Elliott  and Rao  is extremely  useful to researchers/engineers who are working  in the areas of signal processing and communications. It i s also an excellent reference book, and hence a valuable addition to one’s library

http://ieeexplore.ieee.org/iel5/5/31347/01457444.pdf

Multirate digital signal processing

Advancements in the field of autonomous underwater vehicle

Breast cancer is one of the major causes of death among women. Small clusters of micro calcifications appearing as collection of white spots on mammograms show an early warning of breast cancer. Primary prevention seems impossible since the causes of this disease is still remain unknown. An improvement of early diagnostic techniques is critical for women’s quality of life. Mammography is the main test used for screening and early diagnosis. Early detection performed on X-ray mammography is the key to improve breast cancer prognosis. In order to increase radiologists diagnostic performance, several computer-aided diagnosis (CAD) schemes have been developed to improve the detection of primary signatures of this disease: masses and micro calcifications. Masses are space-occupying lesions, described by their shapes, margins, and denseness properties. A benign neoplasm is smoothly marginated, whereas a malignancy is characterized by an indistinct border that becomes more speculated with time. Because of the slight differences in X-ray attenuation between masses and benign glandular tissue, they appear with low contrast and often very blurred. Micro calcifications are tiny deposits of calcium that appear as small bright spots in the mammogram. This paper presents a research on mammography images using Morphological operators and Fuzzy c – means clustering for cancer tumor mass segmentation. The first step of the cancer signs detection should be a segmentation procedure able to distinguish masses and micro calcifications from background tissue using Morphological operators and finally fuzzy c- means clustering (FCM) algorithm has been implemented for intensity – based segmentation. The proposed technique shows better results

http://www.jatit.org/volumes/research-papers/Vol5No6/7Vol5No6.pdf

Automatic detection of breast cancer mass in mammograms using morphological operators and fuzzy c -means clustering

A new method of target tracking by EKF using bearing and elevation measurements for underwater environment

Summary Retinal image analysis is an essential step in the diagnosis of various eye diseases. Diabetic Retinopathy (DR) is globally the primary cause of visual impairment and blindness in diabetic patients. Early diagnosis through regular screening and timely treatment has proven beneficial in preventing visual impairment and blindness. In this paper we have proposed a novel approach to automatically detect diabetic retinopathy from digital fundus images. The digital fundus images are segmented employing morphological operations to identify the regions showing signs of diabetic retinopathy such as hard exudates, soft exudates and the red lesions: microaneurysm and haemorrhages. Various color space values of the segmented regions are calculated. A fuzzy set is formed with the color space values and fuzzy rules are derived based on fuzzy logic reasoning for the detection of diabetic retinopathy. Experimental evaluation on the publicly available dataset DIARETDB0 demonstrates the improved performance of the proposed approach in the diagnosis of diabetic retinopathy.

/pdf/automatic-detection-of-hard-exudates-in-diabetic-retinopathy-3xfeecg6dj.pdf

Automatic Detection of Hard Exudates in Diabetic Retinopathy Using Morphological Segmentation and Fuzzy Logic

Advanced Morphological Technique for Automatic Brain Tumor Detection and Evaluation of Statistical Parameters

Medical image processing is a highly challenging field. Medical image techniques are used to mage the inner portions of the human body for medical diagnosis. MR Images are widely used in the diagnosis of brain tumor. In this paper, we present an automated method to detect and segment the brain tumor regions. The proposed method consists of three main steps, initial segmentation, modeling of energy function and optimize the energy function. To make our segmentation more reliable we use information present in the T1 and FLAIR MRI images. We use conditional random field(CRF) based frame work to combined the information present in T1 and FLAIR in probabilistic domain. Main advantages of CRF based frame work is we can mode complex shapes easily and we incorporate the observation of energy function.

K. Satya Prasad

Papers

Automatic detection of breast cancer mass in mammograms using morphological operators and fuzzy c -means clustering

A new method of target tracking by EKF using bearing and elevation measurements for underwater environment

Automatic Detection of Hard Exudates in Diabetic Retinopathy Using Morphological Segmentation and Fuzzy Logic

Advanced Morphological Technique for Automatic Brain Tumor Detection and Evaluation of Statistical Parameters

Brain Tumor Detection and Segmentation Using Conditional Random Field