In this paper, we describe an approach for the automatic modality classification in medical image retrieval task of the 2010 CLEF cross-language image retrieval campaign (ImageCLEF). This work is focused on the process of feature extraction from medical images and fusion the different extracted visual feature and textual feature for modality classification. To extract visual features from the i...

Abstract In this paper we examine the Single Program Multiple Data (SPMD) parallel implementation of image classification algorithms on a cluster comprised of personal computers. The small-scale cluster environment employed utilizes two quite different Application Programming Interfaces (APls) for inter-process communications, message passing and virtual shared memory. We quantitatively compare...

since most common form of cervical cancer starts with pre-cancerous changes, a flawless detection of these changes becomes an important issue to prevent and treat the cervix cancer. there are 2 ways to stop this disease from developing. one way is to find and treat pre-cancers before they become true cancers, and the other is to prevent the pre-cancers in the first place. the presented approach...

a multi‑parameter quantification method was implemented to quantify retinal vascular injuries in microscopic images of clinically relevant eye diseases. this method was applied to wholemount retinal trypsin digest images of diabetic akita/+, and bcl‑2 knocked out mice models. five unique features of retinal vasculature were extracted to monitor early structural changes and retinopathy, as well ...

Brain tumor is one of the foremost causes for the increase in mortality among children and adults. Computer visions are being used by doctors to analysis and diagnose the medical problems. Magnetic Resonance Imaging (MRI) is a medical imaging technique, which is used to visualize internal structures of MRI brain images for analyzing normal and abnormal prototypes of brain while diagnosing. It i...

---------------------------------------------------------------------***--------------------------------------------------------------------Abstract The ever increasing amounts of patients data in the form of medical images, imposes new challenges to clinical routine such as diagnosis, treatment and monitoring. Image mining is the process of searching and discovering valuable information knowle...

Today, clinicians rely on medical images for screening, diagnosis, treatment planning and follow up, but still a generic and flexible medical image understanding is missing. Although, there exist several approaches for semantic image annotation, those approaches do not make use of practical clinical knowledge, such as best practice solutions or clinical guidelines. Our final goal is to enhance ...

classifying remote sensing imageries to obtain reliable and accurate landuse/cover (luc) information still remains a challenge that depends on many factors suchas complexity of landscape especially in arid region. the aim of this paper is to extractreliable luc information from land sat imageries of the pishkouh watershed of centralarid region, iran. the classical maximum likelihood classifier ...

With a widespread use of digital imaging data in hospitals, the size of medical image repositories is increasing rapidly. This causes difficulty in managing and querying these large databases leading to the need of content based medical image retrieval (CBMIR) systems. A major challenge in CBMIR systems is the semantic gap that exists between the low level visual information captured by imaging...