Developed as a comprehensive solution, QCA provides an unprecedented scope of functionality for analyzing crisp, multi-value and fuzzy sets. The reader is not required to have knowledge of R, but the book assumes an understanding of the fundamentals of QCA. Although mainly written for political scientists, this book is also of interest to scholars from other disciplines in the social sciences such as sociology, business, management, organization, anthropology, education and health.
That Missing Guide In The Your Smart Life Today! Analytical Cellular Pathology, 21 2 —69, Chemoprevention of oral cancer. In Cancer Chemoprevention,pages — Pathology-Research and Practice, 2 —, Application of structural pattern recognition in histopathology. In Syntactic and structuralpattern recognition, pages — Analysis of adenomatous structures in histopathology. Syntactic structure analysis of bronchus carcinomas-first results.
Acta Stereol, 4 2 —, TNM stage, immunohistology, syntactic structure analysis and survival in patients with small cell anaplastic carcinoma of the lung.
Journalofcancerresearchandclinicaloncology, 5 —, Three-dimensional image processing for morphometric analysis of epithelium sections. Cytometry, 13 7 —, ECM-aware cell-graph mining for bone tissue modeling and classification. Data mining and knowledge discovery, 20 3 —, Waxman BM.
Routing of multipoint connections. Augmented cell-graphs for automated cancer diagnosis. Spectral analysis of cell-graphs of cancer. Learning the topological properties of brain tumors. Gunduz-Demir C. Mathematical modeling of the malignancy of cancer using graph evolution. Mathematical biosciences, 2 —, Quantification of spatial parameters in 3d cellular constructs using graph theory. BioMed Research International, , Quantitative metric profiles capture three-dimensional temporospatial architecture to discriminate cellular functional states.
BMC medical imaging, 11 1 , Automated classification of inflammation in colon histological sections based on digital microscopy and advanced image analysis. Cytometry Part A, 73 3 —, Automated virtual microscopy of gastric biopsies. Cytometry Part B: Clinical Cytometry, 70 6 —, Cell cluster graph for prediction of biochemical recurrence in prostate cancer patients from tissue microarrays.
Expectation—maximization-driven geodesic active contour with overlap resolution emagacor : Application to lymphocyte segmentation on breast cancer histopathology. Analysis of soft tissue tumors by an attributed minimum spanning tree. Characterization and featuring of histological section images. Pattern recognitionletters, 7 4 —, Dougherty ER.
An introduction to morphological image processing. Tutorial texts in optical engineering, Segmentation and classification of histological images-application of graph analysis and machine learning methods. Zampirolli FdA. Neighborhood graphs built with morphological operators. PloSone, 9 5 :e, Classification of normal colorectal mucosa and adenocarcinoma by morphometry.
Histopathology, 11 9 —, Expert system support using bayesian belief networks in the diagnosis of fine needle aspiration biopsy specimens of the breast.
J Clin Pathol, 47 4 —36, Automated location of dysplastic fields in colorectal histology using image texture analysis. The Journal of pathology, 1 —75, Classification of cervical cell nuclei using morphological segmentation and textural feature extraction. In Intelligent Information Systems, Tissue counter analysis of benign common nevi and malignant melanoma.
International journal of medical informatics, 69 1 —28, Statistical categorization of human histological images. In Image Processing, ICIP Virtual microscopy and grid-enabled decision support for large-scale analysis of imaged pathology specimens. Pattern Recogn. Computer-aided prognosis of neuroblastoma on whole-slide images: Classification of stromal development.
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Symposium on Computer Applications in Medical Care, pages — Histopathological image classification using stain component features on a PLSA model. Morphometric differentiation between responsive tumor cells and mesothelial hyperplasia in second-look operations for ovarian cancer. Human pathology, 24 2 —, Thiran JP and Macq B.
Morphological feature extraction for the classification of digital images of canceroustissues. Morphometrical feature extraction on color histological images for oncological diagnostics. In 5th International Conference on Biomedical Engineering, pages 14—16, A multispectral computer vision system for automatic grading of prostatic neoplasia. Rajpoot K and Rajpoot NM. Hyperspectral colon tissue cell classification. Wavelets as chromatin texture descriptors for the automated identification of neoplastic nuclei. Journal of microscopy, 1 —35, Multiwavelet grading of pathological images of prostate.
Adaptive discriminant wavelet packet transform and local binary patterns for meningioma subtype classification. Kayser K and Stute H.
Pathology-Research and Practice, 5 —, Combined morphometrical and syntactic structure analysis as tools for histomorphological insight into human lung carcinoma growth. Analytical cellular pathology: the journal of the European Society for Analytical Cellular Pathology, 2 3 —, Integrated optical density IOD , syntactic structure analysis, and survival in operated lung carcinoma patients. Pathology-Research and Practice, 11 —, Alteration of integrated optical density and intercellular structure after induction chemotherapy and survival in lung carcinoma patients treated surgically.
Anatomia, histologia, embryologia, 26 2 —, Oncol, —, Carcinoid tumors of the lung: Immuno-and ligandohistochemistry, analysis of integrated optical density, syntactic structure analysis, clinical data, and prognosis of patients treated surgically. Journal of surgical oncology, 63 2 —, Parameters derived from integrated nuclear fluorescence, syntactic structure analysis, and vascularization in human lung carcinomas.
Analytical Cellular Pathology, 15 2 —83, Pathology-ResearchandPractice, 12 —, Texture and object related image analysis inmicroscopic images. DiagnosticPathology,1 1 , Value of morphometry, texture analysis, densitometry, and histometry in the differential diagnosis and prognosis of malignant mesothelioma. The Journal of pathology, 4 —, Determination of tumour prognosis based on angiogenesis-related vascular patterns measured by fractal and syntactic structure analysis. Clinical Oncology, 16 4 —, Automated Grading of Prostate Cancer using architectural and textural image Features.
Automated grading of breast cancer histopathology using spectral clustering with textural and architectural image features. ISBI Cascaded discrimination of normal, abnormal, and confounder classes in histopathology: Gleason grading of prostate cancer. BMC bioinformatics, 13 1 , Using manifold learning for content-based image retrieval of prostate histopathology. Review: Integrated diagnostics: a conceptual framework with examples.
Clinical Chemistry and Laboratory Medicine,—, IEEE Trans. Engineering, 60 8 —, Image analysis based grading of bladder carcinoma. Comparison of object, texture and graph based methods and their reproducibility. Analytical Cellular Pathology, 15 1 :1—18, Exploratory analysis of quantitative histopathology of cervical intraepithelial neoplasia: Objectivity, reproducibility, malignancy-associated changes, and human papillomavirus.
Cytometry Part A, 60 1 —89, Time-efficient sparse analysis of histopathological whole slide images. Computerized medical imaging and graphics, 35 7 — , Interactive classification and content based retrieval of tissue images. Lee LQ and Lumsdaine A.
The development of Qualitative Comparative Analysis (QCA) by Charles Ragin has given SpringerBriefs in Political Science A User's Guide Pages The development of Qualitative Comparative Analysis (QCA) by Charles Ragin has given SpringerBriefs in Political Science Table of contents (5 chapters).
Addison-Wesley Longman Publishing Co. Electronic Notes in Theoretical Computer Science, 5 —45, Analysis and visualization of network data using JUNG. Journal of Statistical Software, 10 2 :1—35, Computational Geometry. Bradski G and Kaehler A. Planar Subdivisions. Guibas L and Stolfi J.
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Datasim Education BV, Liang W. Domiter V and Zcalik B. Sweep-line algorithm for constrained delaunay triangulation. International Journal of Geographical Information Science, 22 4 —, Distributed computing in image analysis using open source frameworks and application to image sharpness assessment of histological whole slide images. Diagn Pathol, 6 Suppl 1 :S16, Scientific Reports, 2, User Username Password Remember me. A review of graph-based methods for image analysis in digital histopathology. Abstract Digital image analysis of histological datasets is a currently expanding field of research.
With different stains, magnifications and types of tissues, histological images are inherently complex in nature and contain a wide variety of visual information. Several image analysis techniques are being explored in this direction.
However, graph-based methods are gaining most popularity, as these methods can describe tissue architecture and provide adequate numeric information for subsequent computer-based analysis. Graphs have the ability to represent spatial arrangements and neighborhood relationships of different tissue components, which are essential characteristics observed visually by pathologists during investigation of specimens. In this paper, we present a comprehensive review of the graph-based methods explored so far in digital histopathology.
We also discuss the current limitations and suggest future directions in graph-based tissue image analysis. Keywords Digital histopathology, graph-based methods, whole slide images, medical image analysis, image understanding, tissue architecture, spatial arrangement. Full Text: PDF. Rolls G. An introduction to specimen preparation. Sucaet Y and Waelput W. Digital Pathology. SpringerBriefs in Computer Science. Trudeau RJ. Introduction to Graph Theory. Dover Publications, New York, In Computational Geometry, pages 1— Fortune S.
A sweepline algorithm for voronoi diagrams.