the genus hyoscyamus belongs to the tribe hyoscyameae miers of solanaceae family. variation in protein bands elaborates the relationship among the collections from various geographical regions. in this study the seed storage protein diversity of 19 accessions of hyoscyamus (h. niger, h. reticulatus and  h. pusillus) from west azerbaijan (iran) was investigated according to the sodium dodecyl su...

in the present study, random amplified polymorphic dna (rapd) and inter-simple sequence repeat (issr) markers were used to estimate genetic diversity and relationships among 35 cluster bean [cyamopsis tetragonoloba (l.) taub] genotypes. for rapd analysis, 20 random primers were used which amplified 164 bands, 147 of which were polymorphic with an average polymorphism of 90.3%. the amplified pro...

Premature infants exhibit widespread insults and delays in white matter maturation that can be sensitively detected early using diffusion tensor imaging. Diffusion tensor tractography facilitates in vivo visualization of white matter tracts and has the potential to be more sensitive than simpler two-dimensional DTI-based measures. However, the reliability and reproducibility of performing tract...

Early detection of skin cancer, particularly melanoma, is crucial to enable advanced treatment. Due to the rapid growth of skin cancers, there is a growing need of computerized analysis for skin lesions. These processes including detection, classification, and segmentation. There are three main types of skin lesions in common that are benign nevi, melanoma, and seborrhoeic keratoses which have ...

BACKGROUND AND PURPOSE High resolution 7T MRI is increasingly used to investigate hippocampal subfields in vivo, but most studies rely on manual segmentation which is labor intensive. We aimed to evaluate an automated technique to segment hippocampal subfields and the entorhinal cortex at 7T MRI. MATERIALS AND METHODS The cornu ammonis (CA)1, CA2, CA3, dentate gyrus, subiculum, and entorhinal...

We present a deep convolutional neural network application based on autoencoders aimed at segmentation of increased signal regions in fluid-attenuated inversion recovery magnetic resonance imaging images. The convolutional autoencoders were trained on the publicly available Brain Tumor Image Segmentation Benchmark (BRATS) data set, and the accuracy was evaluated on a data set where 3 expert seg...

Information on the web is growing exponentially. The unprecedented growth of available information coupled with the vast number of available online activities. It has introduced a new wrinkle to the problem of web search. It is difficult to retrieve relevant information. In this context search engines have become a valuable tool for users to retrieve relevant information. Finding relevant infor...

Random Amplified Polymorphic DNA (RAPD) markers was used to analyze the genetic structure of five Indigenous Egyptian’s chicken populations including Fayoumi, Dokki-4, Golden Montazah, Silver Montazah, and ElSalam, based on the taxa generated by the analysis of ten RAPD markers. The population genetic distances were estimated by using two cluster algorithms (UPGMA & NJ neighbor-joining) accompa...

Accurate segmentation of organs at risk is essential for radiation therapy planning. However, manual time-consuming and prone to inter intra-observer variability. This study proposes a self-supervision based attention UNet model OAR abdominal CT images. The utilizes mechanism train itself without the need annotations. used highlight important features suppress irrelevant ones, thus improving mo...

In this paper we present a new method for cystoid macular edema (CME) segmentation in retinal Optical Coherence Tomography (OCT) images, using a fully convolutional neural network (FCN) and a fully connected conditional random fields (dense CRFs). As a first step, the framework trains the FCN model to extract features from retinal layers in OCT images, which exhibit CME, and then segments CME r...