685 research outputs found
Machine Learning And Pattern Classification In Identification Of Indigenous Retinal Pathology
No full textDiabetic retinopathy (DR) is a complication of diabetes, which if untreated leads to blindness. DR early diagnosis and treatment improve outcomes. Automated assessment of single lesions associated with DR has been investigated for sometime. To improve on classification, especially across different ethnic groups, we present an approach using points-of-interest and visual dictionary that contains important features required to identify retinal pathology. Variation in images of the human retina with respect to differences in pigmentation and presence of diverse lesions can be analyzed without the necessity of preprocessing and utilizing different training sets to account for ethnic differences for instance. © 2011 IEEE.59515954Mitchell, P., Foran, S., Wong, T.Y., Chua, B., Patel, I., Ojaimi, E., (2008) Guidelines for the Management of Diabetic Retinopathy, , Canberra: NHMRCJelinek, H.F., Cornforth, D., Cree, M., Cesar R M, J., Leandro, J.J.G., Soares, J.V.B., Mitchell, P., Automated characterisation of diabetic retinopathy using mathematical morphology: A pilot study for community health (2003) NSW Primary Health Care Research and Evaluation Conference, p. 48. , SydneyCree, M.J., Olson, J.A., McHardy, K., Sharp, P., Forrester, J., A fully automated comparative microaneurysm digital detection system (1997) Eye, 11, pp. 622-628Karperien, A.L., Jelinek, H.F., Leandro, J.J.G., Soares, J.V.B., Cesar R M, J., Luckie, A., Automated detection of proliferative retinopathy in clinical practice (2008) Clinical Ophthalmology, 2, pp. 109-122Wang, H., Hsu, W., Goh, K.G., Lee, M.L., An effective approach to detect lesions in colour retinal images (2000) IEEE Int. Conf. in Computer Vision and Pattern Recognition, pp. 181-187Streeter, L., Cree, M.J., Microaneurysm detection in colour fundus images (2003) Image and Vision Computing, pp. 280-284Goatman, K.A., Cree, M.J., Olson, J.A., Sharp, P.F., Forrester, J.V., Automated measurement of microaneurysm turnover (2003) Investigative Ophthalmology and Visual Science, 44, pp. 5335-5341Cree, M.J., Gamble, E., Cornforth, D.J., Colour normalisation to reduce inter-patient and intra-patient variability in microaneurysm detection in colour retinal images (2005) Workshop on Digital Image Computing, pp. 163-169. , Brisbane, AustraliaValle, E., Cord, M., Philipp-Foliguet, S., High-dimensional descriptor indexing for large multimedia databases (2008) ACM Intl. Conf. on Information and Knowledge Management, pp. 739-748Bay, H., Tuytelaars, T., Gool, L.V., SURF: Speeded up robust features (2006) European Conf. on Computer Vision, pp. 1-14Viola, P., Jones, M., Robust real-time face detection (2004) Intl. Journa of Computer Vision, 52, pp. 137-154Rocha, A., Carvalho, T., Goldenstein, S., Wainer, J., (2011) Points of Interest and Visual Dictionary for Retina Pathology Detection, , Technical Report IC-11-07, Institute of Computing, Univ. of Campinas, Campinas, Brazi
Measuring industry-science links through inventor-author relations: A profiling method
No full textIn this pilot study we examine the performance of text-based profiling in recovering a set of validated inventor-author links. In a first step we match patents and publications solely based on their similarity in content. Next, we compare inventor and author names on the highest ranked matches for the occurrence of name matches. Finally, we compare these candidate matches with the names listed in a validated set of inventor-author names. Our text-based profile methodology performs significantly better than a random matching of patents and publications, suggesting that text-based profiling is a valuable complementary tool to the name searches used in previous studies.innovation; industry-science links; text-based profiling;
Author Correction: New perspectives on Neanderthal dispersal and turnover from Stajnia Cave (Poland)
No full textThe Author contributions section now reads:“W.N., A.N. and S.T. designed research; A.P., M.H., W.N., S.B., M.U., A.M., H.F., M.D.B., P.S., K.S., M.Ż., A.W., A.N. and S.T. performed research; A.P., M.H., W.N., S.B., M.U., A.M., H.F., M.D.B., P.S., K.S., M.Ż., A.W., A.N. and S.T. analysed data; A.P., M.H., S.T., W.N. and S.B. wrote the paper with the collaboration of all the co-authors.
Classification of pathology in diabetic eye disease
No full textProliferative diabetic retinopathy is a complication of diabetes that can eventually lead to blindness. Early identification of this complication reduces the risk of blindness by initiating timely treatment. We report the utility of pattern analysis tools linked with a simple linear discriminant analysis that not only identifies new vessel growth in the retinal fundus but also localises the area of pathology. Ten fluorescein images were analysed using seven feature descriptors including area, perimeter, circularity, curvature, entropy, wavelet second moment and the correlation dimension. Our results indicate that traditional features such as area or perimeter measures of neovascularisation associated with proliferative retinopathy were not sensitive enough to detect early proliferative retinopathy (SNR = 0.76, 0.75 respectively). The wavelet second moment provided the best discrimination with a SNR of 1.17. Combining second moment, curvature and global correlation dimension provided a 100% discrimination (SNR = 1)
Author Correction:A 41,500 year-old decorated ivory pendant from Stajnia Cave (Poland)
No full textCorrection to: Scientific Reports https://doi.org/10.1038/s41598-021-01221-6, published online 25 November 2021The original version of this Article contained errors in the author list where Marjolein D. Bosch was omitted from the author list, and Mikołaj Urbanowski was incorrectly listed as an author of the original Article, and has subsequently been removed.The Author contributions section now reads:“S.T. W.N. and A.N. conceived the project; S.T., W.N., A.P., M.B., S.C., M.D., H.F., A.M., M.D. B., D.P., M.P.R., C.M.R., V.S-M., G.M.S., P.S., M.S., K.S., A.V., F.W., H.W., A.W., M.Z., S.B., A.N., J-J. H., performed research; S.T., A.P., W.N., M.B., M.D.B., S.C., M.D., H.F., A.M., D.P., M.P.R., C.M.R., V.S-M., G.M.S., P.S., M.S., K.S., A.V., F.W., H.W., A.W., M.Z., S.B., A.N., J-J. H. analysed all archaeological data; S.T. and A.P. wrote the paper with the collaboration of all the co-authors.”The original Article and its accompanying Supplementary Information file have been corrected
ASA member experiences and perceptions of the peer reviewing-editing process (Chapter 4)
No full textA membership survey regarding policies and attitudes germane
to the peer reviewing and editing practices and policies
of the American Society of Agronomy, Crop Science Society
of America, and Soil Science Society of America was deemed
worthwhile. A second survey queried agricultural experiment
station directors on related institutional aspects of the same
topic. Briefly, responses indicated good demographic representation
of editorial boards with some underrepresentation of non-U.S.
addressed members. One-third of the membership has
served on the editorial board of some journal, and 1 in 7.4 has
served on the editorial board of a Tri-Society journal. Females
are used as reviewers one-third as often in proportion to their
membership as are males. The publishing membership of the
Tri-Societies is essentially those members with Ph.D.'s. Two-thirds
of the papers submitted to Tri-Society journals require
institutional review before journal submission. There is twice
the support among the membership for dual anonymity (author
and reviewers) as for reviewer anonymity only (the current
policy). Nearly one-half the membership perceived shared
responsibility by authors and editors for accuracy of published
manuscripts. There was strong concern for seeking qualified
reviewers, guaranteeing quality of reviews, admonishing poor
reviewers, and instituting training in the Tri-Societies for writing/reviewing/editing.
Greater openmindedness was supported
for publishing "negative" or unusual results where
methodology and analysis were acceptable. Concern was expressed
about influence networks undermining the fairness of
the review process. Significant support exists for a rapid-publication
journal in the Tri-Societies. Two-and-one-half times
more authors indicated movement away from Tri-Society journals
than to them, with 44% indicating no change. The major
reasons for journal migration were gravitation to journals that
better reflected some recent shift in research focus, and various
aspects of dissatisfaction with Tri-Society journals. Institutional
responses indicated a strong rationale for developing and
endorsing codes of ethics and limiting Tri-Society responsibility
for ethical infractions
Author Co-Citation Analysis (ACA): a powerful tool for representing implicit knowledge of scholar knowledge workers
No full textIn the last decade, knowledge has emerged as one of the most important and valuable organizational assets. Gradually this importance caused to emergence of new discipline entitled ―knowledge management‖. However one of the major challenges of knowledge management is conversion implicit or tacit knowledge to explicit knowledge. Thus Making knowledge visible so that it can be better accessed, discussed, valued or generally managed is a long-standing objective in knowledge management. Accordingly in this paper author co- citation analysis (ACA) will be proposed as an efficient technique of knowledge visualization in academia (Scholar knowledge workers)
Advancing Bag-of-Visual-Words Representations for Lesion Classification in Retinal Images
No full textDiabetic Retinopathy (DR) is a complication of diabetes that can lead to blindness if not readily discovered. Automated screening algorithms have the potential to improve identification of patients who need further medical attention. However, the identification of lesions must be accurate to be useful for clinical application. The bag-of-visual-words (BoVW) algorithm employs a maximum-margin classifier in a flexible framework that is able to detect the most common DR-related lesions such as microaneurysms, cotton-wool spots and hard exudates. BoVW allows to bypass the need for pre- and post-processing of the retinographic images, as well as the need of specific ad hoc techniques for identification of each type of lesion. An extensive evaluation of the BoVW model, using three large retinograph datasets (DR1, DR2 and Messidor) with different resolution and collected by different healthcare personnel, was performed. The results demonstrate that the BoVW classification approach can identify different lesions within an image without having to utilize different algorithms for each lesion reducing processing time and providing a more flexible diagnostic system. Our BoVW scheme is based on sparse low-level feature detection with a Speeded-Up Robust Features (SURF) local descriptor, and mid-level features based on semisoft coding with max pooling. The best BoVW representation for retinal image classification was an area under the receiver operating characteristic curve (AUC-ROC) of 97.8% (exudates) and 93.5% (red lesions), applying a cross-dataset validation protocol. To assess the accuracy for detecting cases that require referral within one year, the sparse extraction technique associated with semi-soft coding and max pooling obtained an AUC of 94.2±2.0%, outperforming current methods. Those results indicate that, for retinal image classification tasks in clinical practice, BoVW is equal and, in some instances, surpasses results obtained using dense detection (widely believed to be the best choice in many vision problems) for the low-level descriptors. © 2014 Pires et al.96Sinthanayothin, C., Boyce, J.F., Williamson, T.H., Cook, H.L., Mensah, E., Lal, S., Usher, D., Automated detection of diabetic retinopathy on digital fundus images (2002) Diabetic Medicine, 19 (2), pp. 105-112. , DOI 10.1046/j.1464-5491.2002.00613.xJelinek, H.F., Cree, M.J., Worsley, D., Luckie, A.P., Nixon, P., An automated microaneurysm detector as a tool for identification of diabetic retinopathy in rural optometric practice (2006) Clinical and Experimental Optometry, 89, pp. 299-305Fleming, A.D., Philip, S., Goatman, K.A., Olson, J.A., Sharp, P.F., Automated microaneurysm detection using local contrast normalization and local vessel detection (2006) IEEE Transactions on Medical Imaging, 25 (9), pp. 1223-1232. , DOI 10.1109/TMI.2006.879953, 1677728Niemeijer, M., Van Ginneken, B., Russell, S.R., Suttorp-Schulten, M.S.A., Abramoff, M.D., Automated detection and differentiation of drusen, exudates, and cotton-wool spots in digital color fundus photographs for diabetic retinopathy diagnosis (2007) Investigative Ophthalmology and Visual Science, 48 (5), pp. 2260-2267. , DOI 10.1167/iovs.06-0996Giancardo, L., Mériaudeau, F., Karnowski, T.P., Tobin, K.W., Li, Y., Microaneurysms Detection with the Radon Cliff Operator in Retinal Fundus Images (2010) SPIE Medical Imaging, pp. 76230U-76230U. , International Society for Optics and PhotonicsAntal, B., Hajdu, A., An Ensemble-based System for Microaneurysm Detection and Diabetic Retinopathy Grading (2012) IEEE Transactions on Biomedical Engineering, 59 (6), pp. 1720-1726Lazar, I., Hajdu, A., Retinal Microaneurysm Detection Through Local Rotating Cross-section Profile Analysis (2013) IEEE Transactions on Medical Imaging, 32 (2), pp. 400-407Zhang, B., Wu, X., You, J., Li, Q., Karray, F., Hierarchical Detection of Red Lesions in Retinal Images by Multiscale Correlation Filtering (2009) SPIE Medical Imaging, pp. 72601L-72601L. , International Society for Optics and PhotonicsSánchez, C.I., Hornero, R., Mayo, A., García, M., Mixture model-based clustering and logistic regression for automatic detection of microaneurysms in retinal images (2009) SPIE Medical Imaging, pp. 72601M-72601M. , International Society for Optics and PhotonicsSánchez, C.I., García, M., Mayo, A., López, M.I., Hornero, R., Retinal image analysis based on mixture models to detect hard exudates (2009) Medical Image Analysis, 13 (4), pp. 650-658Giancardo, L., Meriaudeau, F., Karnowski, T.P., Li, Y., Garg, S., Tobin, K.W., Chaum, E., Exudate-based diabetic macular edema detection in fundus images using publicly available datasets (2012) Medical Image Analysis, 16 (1), pp. 216-226Fleming, A.D., Philip, S., Goatman, K.A., Williams, G.J., Olson, J.A., Sharp, P.F., Automated detection of exudates for diabetic retinopathy screening (2007) Physics in Medicine and Biology, 52 (24), pp. 7385-7396. , DOI 10.1088/0031-9155/52/24/012, PII S0031915507570430Sopharak, A., Uyyanonvara, B., Barman, S., Williamson, T.H., Automatic detection of diabetic retinopathy exudates from non-dilated retinal images using mathematical morphology methods (2008) Computerized Medical Imaging and Graphics, 32, p. 8Welfer, D., Scharcanski, J., Marinho, D.R., A coarse-to-fine strategy for automatically detecting exudates in color eye fundus images (2010) Computerized Medical Imaging and Graphics, 34, pp. 228-235Boureau, Y., Bach, F., LeCun, Y., Ponce, J., Learning mid-level features for recognition (2010) IEEE Intl. Conference on Computer Vision and Pattern RecognitionRocha, A., Carvalho, T., Jelinek, H.F., Goldenstein, S., Wainer, J., Points of interest and visual dictionaries for automatic retinal lesion detection (2012) IEEE Transactions on Biomedical Engineering, 59, pp. 2244-2253Jelinek, H.F., Rocha, A., Carvalho, T., Goldenstein, S., Wainer, J., Machine learning and pattern classification in identification of indigenous retinal pathology (2011) Intl. Conference of the IEEE Engineering in Medicine and Biology Society, pp. 5951-5954Jelinek, H.F., Pires, R., Padilha, R., Goldenstein, S., Wainer, J., Data fusion for multi-lesion diabetic retinopathy detection (2012) IEEE Intl. Computer-Based Medical Systems, pp. 1-4Phillips, P.J., Visible manifestations of diabetic retinopathy (2012) Medicine Today, 5, p. 83(2013) Diabetes Programme. 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De tinertsafzettingen van het eiland Singkep en de genese der alluviale afzettingen
No full textCivil Engineering and Geoscience
Metasomatische Probleme (Mount Isa, Rammelsberg, Meggen, Mansfeld und künstliche Verdrängung)
No full textCivil Engineering and Geoscience
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