Current Signal Transduction Therapy - Volume 11, Issue 2, 2016

Background: Digital Mammography is the most vital and successful imaging modality used by radio diagnosis method to find out breast cancer. Breast cancer is the most significant and common cause of cancer death in women. The main problem is to find the accurate and efficient method for breast cancer segmentation. Method: The morphological method is the most important approach in image segmentation method. T Read More

Background: Colon cancer remains among the top perpetrators of deaths linked to cancer. The probability of cancer reaching more parts of the body is extremely high in colorectal cancers. Early detection is hence, highly important for faster treatment. Method: In the current work, a hybrid approach toward the detection of colon cancers through the usage of microarray datasets, is presented. Particle Swarm Optimization (P Read More

Background: Microarray technologies provide huge amount of information and is particularly helpful in the prediction and diagnosis of cancer. To accurately classify cancers, genes related to cancer have to be selected, as genes mined from microarrays possess too much noise. Method: In the current work, new binary modifications of the Grey Wolf Optimization (GWO) is suggested for choosing optimal features subsets for clas Read More

Background: Mammographies are a significant technology utilized in the effective detection of breast cancers prior to them becoming palpable during selfexaminations. The primary aim of the study was the determination of screening precision of mammographies as well as ultrasounds in local populations. Method: In the current study, Minimum Spanning Tree (MST) segmentations are suggested for the selection of minute Read More

Background: Neural Networks are utilized in several applications in the field of healthcare, one such being the classification of lung cancers. Innovative advancements in diagnosing tumours are a major boost to developing novel treatment techniques in the early stages of lung cancer. Method: In this work, a novel image-based features selection method for classifying lung Computed Tomography (CT) images is introduc Read More

Background: Breast cancers are one of the most prevalent forms of cancers amongst women apart from being the top second cause of cancer related deaths across the world. A way to detect the presence of breast cancers earlier is through the presence of minute deposits of calcium, that is, micro-calcifications in mammograms. Detecting this much earlier is important for successfully treating the cancer. Method: In the cur Read More

Background: Breast cancers are conventionally the leading cause of cancer-related deaths amongst women. For the reduction of death rates by earlier identification of carcinogenic areas, mammogram images are utilized. Computer aided diagnosis plays an important role in screening of the mammograms. Mammography is an efficient as well as feasible method for the detection of breast cancers, especially minute tumours. Read More

Applications of medical images are increasing rapidly, moreover the medical images produced by the imaging devices occupies more volume of space. Medical information system needs to store huge amount of data in the form of medical images for future record and also these images are required to be transmitted over network to the place of specialist to obtain diagnostics opinion. Because of the limited availability of spa Read More

Background: Automated Medical Image Analysis has emerged as an important tool for the diagnoses of anatomical pathology and can be integrated with the medical information system to deliver useful information for the health care provider. Method: This study proposes a novel SVM Classifier Using Soft Computing Approach for Automated Classification of Emphysema, Bronchiectasis and Pleural Effusion Using Optimiz Read More

Background: Segmenting images is the most difficult as well as a happening research topic in the domain of image processing. Despite accessibility to a huge number of excellent approaches for brain Magnetic Resonance Imaging (MRI) segmentations, it remains a difficult job and speed of the technique requires great improvements. Medical images segmentations need effective as well as strong segmentation models that are r Read More