Citations Report

Imaging in Medicine : Citations & Metrics Report

Articles published in Imaging in Medicine have been cited by esteemed scholars and scientists all around the world.

Imaging in Medicine has got h-index 25, which means every article in Imaging in Medicine has got 25 average citations.

Following are the list of articles that have cited the articles published in Imaging in Medicine.

• Kwak JT, Xu S, Pinto PA, Turkbey B, Bernardo M, Choyke PL, Wood BJ. A multiview boosting approach to tissue segmentation. InSPIE Medical Imaging 2014 Apr 11 (pp. 90410R-90410R). International Society for Optics and Photonics. View at Publisher | View at Google Scholar
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• Akbar S, Jordan LB, Purdie CA, et al. Comparing computer-generated and pathologist-generated tumour segmentations for immunohistochemical scoring of breast tissue microarrays. British journal of cancer. 113,1075-1080 (2015). View at Publisher | View at Google Scholar
• Sridhar A, Doyle S, Madabhushi A. Content-based image retrieval of digitized histopathology in boosted spectrally embedded spaces. Journal of pathology informatics. 6 (2015). View at Publisher | View at Google Scholar | View at Indexing
• Ramos-Pollán R, Cruz-Roa A, González FA. A framework for high performance image analysis pipelines. InComputing Congress (CCC), 2012 7th Colombian 2012 Oct 1 (pp. 1-6). IEEE. View at Publisher | View at Google Scholar
• Peikari M, Gangeh MJ, Zubovits J, Clarke G, Martel AL. Triaging diagnostically relevant regions from pathology whole slides of breast cancer: A texture based approach. IEEE transactions on medical imaging.35,307-315 (2016). View at Publisher | View at Google Scholar
• KÃ¥rsnäs A, Strand R, Doré J, Ebstrup T, Lippert M, Bjerrum K. A histopathological tool for quantification of biomarkers with sub-cellular resolution. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization. 3,25-46 (2015). View at Publisher | View at Google Scholar
• Khan AM. Algorithms for breast cancer grading in digital histopathology images (Doctoral dissertation, University of Warwick). View at Publisher | View at Google Scholar
• KÃ¥rsnäs A. Image analysis methods and tools for digital histopathology applications relevant to breast cancer diagnosis (Doctoral dissertation, Acta Universitatis Upsaliensis). View at Publisher | View at Google Scholar | View at Indexing
• Arevalo J, Cruz-Roa A, GONZÁLEZ O FA. Histopathology image representation for automatic analysis: A state-of-the-art review. Revista Med. 2014 Dec;22(2):79-91. View at Publisher | View at Google Scholar | View at Indexing
• Hernández-Cabronero M, Auli-Llinas F, Sanchez V, Sagristà JS. Transform optimization for the Lossy Coding of pathology whole-slide images. InData Compression Conference (DCC), 2016 2016 Mar 30 (pp. 131-140). IEEE. View at Publisher | View at Google Scholar
• Song JW, Lee JH. New morphological features for grading pancreatic ductal adenocarcinomas. BioMed research international. (2013) View at Publisher | View at Google Scholar
• Abid D. Segmentation of Tumor Regions in Microscopic Images of Breast Cancer Tissue (Doctoral dissertation, QATAR UNIVERSITY). View at Publisher | View at Google Scholar
• Wright AI, Magee DR, Quirke P, Treanor DE. Prospector: A web-based tool for rapid acquisition of gold standard data for pathology research and image analysis. Journal of pathology informatics. 6 (2015). View at Publisher | View at Google Scholar
• Janowczyk A, Chandran S, Feldman M, Madabhushi A. Local morphologic scale: application to segmenting tumor infiltrating lymphocytes in ovarian cancer TMAs. InSPIE Medical Imaging 2011 Mar 3 (pp. 79622N-79622N). International Society for Optics and Photonics. View at Publisher | View at Google Scholar
• Manera M, Giari L, De Pasquale JA, Dezfuli BS. Local connected fractal dimension analysis in gill of fish experimentally exposed to toxicants. Aquatic Toxicology. 175,12-9 (2016) . View at Publisher | View at Google Scholar | View at Indexing
• Kumar R, Srivastava R. Cancer Detection from Microscopic Biopsy Images Using Image Processing and Pattern Recognition Tools: A Review. Journal of Medical Imaging and Health Informatics. 5,877-892 (2015). View at Publisher | View at Google Scholar
• Lindner M, Shotan Z, Garini Y. Rapid microscopy measurement of very large spectral images. Optics express. 24,9511-9527 (2016). View at Publisher | View at Google Scholar
• Sanchez V, Hernandez-Cabronero M, Auli-Llinàs F, Serra-Sagristà J. Fast lossless compression of whole slide pathology images using HEVC intra-prediction. InAcoustics, Speech and Signal Processing (ICASSP), 2016 IEEE International Conference on 2016 Mar 20 (pp. 1456-1460). IEEE. View at Publisher | View at Google Scholar
• Hahn HK, Harz MT, Seyffarth H, Zöhrer F, Böhler T, Filippatos K, Wang L, Homeyer A, Ritter F, Laue H, Günther M. Concepts for efficient and reliable multi-modal breast image reading. InInternational Workshop on Digital Mammography 2010 Jun 16 (pp. 121-128). Springer Berlin Heidelberg. View at Publisher | View at Google Scholar
• Saxena P, Tripathi KC, Hrisheekesha PN. International journal of Computing. View at Publisher | View at Google Scholar
• Hernández-Cabronero M, Sanchez V, Aulí-Llinàs F, Serra-Sagristà J. Fast MCT optimization for the compression of whole-slide images. InImage Processing (ICIP), 2016 IEEE International Conference on 2016 Sep 25 (pp. 2370-2374). IEEE. View at Publisher | View at Google Scholar
• Kim E, Mente S, Keenan A, Gehlot V. Digital Pathology Annotation Data for Improved Deep Neural Network Classification. InSPIE Medical Imaging 2017 Mar 13 (pp. 101380D-101380D). International Society for Optics and Photonics. View at Publisher | View at Google Scholar
• Jia Z, Huang X, Chang EI, Xu Y. Constrained Deep Weak Supervision for Histopathology Image Segmentation. arXiv preprint arXiv:1701.00794. 2017 Jan 3. View at Publisher | View at Google Scholar | View at Indexing
• Zarei N, Bakhtiari A, Korbelik J, Carraro A, Keyes M, MacAulay C. AQCHANALYTICAL AND. View at Publisher | View at Google Scholar
• Manera M, Dezfuli BS, DePasquale JA, Giari L. Multivariate approach to gill pathology in European sea bass after experimental exposure to cadmium and terbuthylazine. Ecotoxicology and environmental safety. 129,282-290 (2016). View at Publisher | View at Google Scholar
• Roa AC, Romero E, González F. An adaptive image representation learned from data for Cervix cancer tumor detection. InSPIE Medical Imaging 2013 Mar 29 (pp. 86760Q-86760Q). International Society for Optics and Photonics. View at Publisher | View at Google Scholar
• Srinivas U. Discriminative models for robust image classification. arXiv preprint arXiv:1603.02736. (2016) View at Publisher | View at Google Scholar
• Cruz-Roaa A, Caicedoa JC, Gonzáleza FA. Visual pattern mining in histology image collections using bag of.
• Noori Hoshyar A. Automatic skin cancer detection system (Doctoral dissertation). View at Publisher | View at Google Scholar
• Makandar A, Halalli B. Breast Cancer Detection and Classification using Microscopic Image. View at Publisher | View at Google Scholar
• Saxena S, Shukla KK, Sharma S. Cellular Image Segmentation using Morphological Operators and Extraction of Features for Quantitative Measurement. Biosciences Biotechnology Research Asia. 13,1101-1112 (2016). View at Publisher | View at Google Scholar
• Arevalo J, Cruz-Roa A. Representación de imágenes de histopatología utilizada en tareas de análisis automático: estado del arte. Revista Med. 22,79 (2014). View at Publisher | View at Google Scholar
• Janowczyk A, Chandran S, Madabhushi A, inventors; Rutgers, assignee. High-throughput biomarker segmentation utilizing hierarchical normalized cuts. United States patent US 9,111,179 (2015). View at Publisher | View at Google Scholar
• Sparks R. Linking and characterizing biologic scales of imaging data: applications to prostate cancer diagnosis (Doctoral dissertation, Rutgers University-Graduate School-New Brunswick). View at Publisher | View at Google Scholar
• Cruz-Roa Á, Ramos-Pollán R, González FA. A Framework for High Performance Image Analysis Pipelines. View at Publisher | View at Google Scholar
• Fakhrzadeh A, Spörndly‐Nees E, Ekstedt E, Holm L, Luengo Hendriks CL. New computerized staging method to analyze mink testicular tissue in environmental research. Environmental Toxicology and Chemistry. 36,156-164 (2017). View at Publisher | View at Google Scholar
• Sparks R, Madabhushi A. Out-of-Sample Extrapolation utilizing Semi-Supervised Manifold Learning (OSE-SSL): Content Based Image Retrieval for Histopathology Images. Scientific reports. 6 (2016). View at Publisher | View at Google Scholar
• Xu J, Sparks R, Janowczyk A, Tomaszewski JE, Feldman MD, Madabhushi A. High-throughput prostate cancer gland detection, segmentation, and classification from digitized needle core biopsies. InInternational Workshop on Prostate Cancer Imaging 2010 Sep 24 (pp. 77-88). Springer, Berlin, Heidelberg. View at Publisher | View at Google Scholar | View at Indexing
• Zhao W, Yang S, Yang J, Li J, Zheng J, Qing Z, Yang R. Visual Biopsy by Hydrogen Peroxide-Induced Signal Amplification. Analytical Chemistry. 88,10728-10735 (2016). View at Publisher | View at Google Scholar
• Saxena P, Singh SK, Agrawal P. A heuristic approach for determining the shape of nuclei from H&E stained imagery. InEngineering and Systems (SCES), 2013 Students Conference on 2013 Apr 12 (pp. 1-6). IEEE. View at Publisher | View at Google Scholar

• Sridhar A. Content-based image retrieval of digitized histopathology via boosted spectral embedding (BoSE) (Doctoral dissertation, Rutgers University-Graduate School-New Brunswick).

  View at Publisher | View at Google Scholar
• Sen B, Vedanarayanan V. Efficient Classification of Breast Lesion based on Deep Learning Technique. Bonfring International Journal of Advances in Image Processing. 6,1 (2016). View at Publisher | View at Google Scholar
• Sridhar A. Content-based image retrieval of digitized histopathology via boosted spectral embedding (BoSE) (Doctoral dissertation, Rutgers University-Graduate School-New Brunswick). View at Publisher | View at Google Scholar
• Madabhushia A. Selective invocation of shape priors for deformable segmentation and morphologic classification of prostate cancer tissue microarrays. View at Publisher | View at Google Scholar
• Reeja R, Romalt AA. Ovarian Cancer Detection using Hierarchical Normalized Cuts. InProceedings of the International Conference on Applied Mathematics and Theoretical Computer Science 274 (2013). View at Publisher | View at Google Scholar
• Kwak JT. Computational methods for cancer diagnosis and prognosis from FT-IR spectroscopy data (Doctoral dissertation, University of Illinois at Urbana-Champaign). View at Publisher | View at Google Scholar
• Hatipoglu N, Bilgin G. Feature extraction for histopathological images using Convolutional Neural Network. InSignal Processing and Communication Application Conference (SIU), 2016 24th 2016 May 16 (pp. 645-648). IEEE. View at Publisher | View at Google Scholar
• Cruz Roa AA. Data-driven Representation Learning from Histopathology Image Databases to Support Digital Pathology Analysis (Doctoral dissertation, Universidad Nacional de Colombia-Sede Bogotá). View at Publisher | View at Google Scholar
• Hatipoglu N, Bilgin G. Feature extraction for histopathological images using Convolutional Neural Network. InSignal Processing and Communication Application Conference (SIU), 2016 24th 2016 May 16 (pp. 645-648). IEEE. View at Publisher | View at Google Scholar

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