classification and content based retrieval of digital mammograms and placental sonograms

Image processing has been a challenging and multidisciplinary research area since decades with continuing improvements in its various branches especially Medical Imaging. The healthcare industry was very much benefited with the advances in Image Processing techniques for the efficient management of large volumes of clinical data. The popularity and growth of Image Processing field attracts researchers from many disciplines including Computer Science and Medical Science due to its applicability to the real world. In the meantime, Computer Science is becoming an important driving force for the further development of Medical Sciences. The objective of this study is to make use of the basic concepts in Medical Image Processing and develop methods and tools for clinicians’ assistance. This work is motivated from clinical applications of digital mammograms and placental sonograms, and uses real medical images for proposing a method intended to assist radiologists in the diagnostic process. The study consists of two domains of Pattern recognition, Classification and Content Based Retrieval. Mammogram images of breast cancer patients and placental images are used for this study. Cancer is a disaster to human race. The accuracy in characterizing images using simplified user friendly Computer Aided Diagnosis techniques helps radiologists in detecting cancers at an early stage. Breast cancer which accounts for the major cause of cancer death in women can be fully cured if detected at an early stage. Studies relating to placental characteristics and abnormalities are important in foetal monitoring. The diagnostic variability in sonographic examination of placenta can be overlooked by detailed placental texture analysis by focusing on placental grading. The work aims on early breast cancer detection and placental maturity analysis. This dissertation is a stepping stone in combing various application domains of healthcare and technology.

Using open source software for digital libraries A case study of CUSAT

The purpose of this paper is to describe the design and development of a digital library at Cochin University of Science and Technology (CUSAT), India, using DSpace open source software. The study covers the structure, contents and usage of CUSAT digital library. Design/methodology/approach – This paper examines the possibilities of applying open source in libraries. An evaluative approach is carried out to explore the features of the CUSAT digital library. The Google Analytics service is employed to measure the amount of use of digital library by users across the world. Findings – CUSAT has successfully applied DSpace open source software for building a digital library. The digital library has had visits from 78 countries, with the major share from India. The distribution of documents in the digital library is uneven. Past exam question papers share the major part of the collection. The number of research papers, articles and rare documents is less. Originality/value – The study is the first of its type that tries to understand digital library design and development using DSpace open source software in a university environment with a focus on the analysis of distribution of items and measuring the value by usage statistics employing the Google Analytics service. The digital library model can be useful for designing similar systems