1,720,955 research outputs found
Latest Trends in Automatic Glioma Tumor Segmentation and an Improved Convolutional Neural Network based Solution
No full textA Brain tumor is an abnormal cell growth in the brain tissues, these tumors are difficult to treat and severely affect the patient's cognitive ability. Out of all brain tumors, gliomas are the deadliest with the least survival rate. The focus of brain tumor segmentation task is to separate tumor tissue such as edema, tumor core from the healthy tissues i.e. white cells, Cerebrospinal Fluid and gray matter. Manual diagnosis of brain tumors from a large amount of patient's MRI images is a tough and time-taking process. With the advent of new approaches, automatic segmentation processes are becoming more effective and clinically accepted. This paper aims to give a comprehensive review of the most state of the art brain tumor segmentation methods. We have given a brief introduction to the imaging modalities and their usage in brain tumor segmentation task We have discussed the results of the most effective approaches by comparing their Dice Score results. We have also discussed some publicly available brain datasets. Furthermore, we have presented a Novel approach for Glioma tumor segmentation using ResNeXt architecture. Experimental results prove that our framework performs well on the dice score
Automatic Prostate Cancer Grading Using Deep Architectures
No full textProstate cancer is the second most aggressive type of cancer among men aged over 45, and it has a major effect on people's lives. Early diagnosis and grading of prostate cancer from tissue images is necessary. Large scale inter observer reproducibility exists in grading the prostate biopsies. This leads us to move towards a computer based model that can accurately detect and grade the cancerous prostate from non-cancerous one. The paper is focused on deep learning based models to automatically grade the prostate cancer from tissue microarray images. Deep learning models directly learn the features via convolutional layers. Two datasets have been used for implementation of our proposed model, Harvard dataset and Gleason Challenge 2019. Our proposed UNET based architecture is used for training as well as validation and testing. We used four different deep learning models, VGG19, ResNet50, Mobilenetv2 and ResNext50 for our UNET based encoder. With our proposed framework, we have achieved 0.728 and 0.732 average Cohen's kappa with F1 on both datasets respectively. The results show that our proposed UNET based deep learning model shows better performance as compared to other state of the art models
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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