1.

Record Nr.

UNISA996466772303316

Autore

Kreck Matthias <1947->

Titolo

Bordism of diffeomorphisms and related topics / / Matthias Kreck ; with an appendix by Neal W. Stoltzfus

Pubbl/distr/stampa

Berlin : , : Springer-Verlag, , 1984

ISBN

3-540-38912-1

Edizione

[1st ed. 1984.]

Descrizione fisica

1 online resource (VI, 150 p.)

Collana

Lecture notes in mathematics ; ; 1069

Classificazione

57R50

57R65

57R90

Disciplina

514.72

Soggetti

Cobordism theory

Cell aggregation - Mathematics

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Bibliographic Level Mode of Issuance: Monograph

Nota di bibliografia

Includes bibliographical references and index.

Nota di contenuto

Bordism groups of orientation preserving diffeomorphisms -- Report about equivariant Witt groups -- The isometric structure of a diffeomorphism -- The mapping torus of a diffeomorphism -- Fibrations over S1 within their bordism class and the computation of ?* -- Addition and subtraction of handles -- Proof of Theorem 5.5 in the odd-dimensional case -- Proof of Theorem 5.5 in the even-dimensional case -- Bordism of diffeomorphisms on manifolds with additional normal structures like Spin-, unitary structures or framings; orientation reversing diffeomorphisms and the unoriented case -- Application to SK-groups -- Miscellaneous results: Ring structure, generators, relation to the inertia group.



2.

Record Nr.

UNINA9910861092303321

Autore

Samantaray Aswini Kumar

Titolo

Feature Extraction in Medical Image Retrieval : A New Design of Wavelet Filter Banks / / by Aswini Kumar Samantaray, Amol D. Rahulkar

Pubbl/distr/stampa

Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024

ISBN

3-031-57279-3

Edizione

[1st ed. 2024.]

Descrizione fisica

1 online resource (162 pages)

Altri autori (Persone)

RahulkarAmol D

Disciplina

621,382

Soggetti

Image processing

Biomedical engineering

Materials - Analysis

Imaging systems

Image Processing

Medical and Health Technologies

Imaging Techniques

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di contenuto

Content Based Medical Image Retrieval -- Fundamentals of Wavelet Filter Banks -- Fundamentals of Gabor Wavelet Filter Banks -- A Family of Multiplier Free Orthogonal Wavelet Filter Banks -- Design of Symmetric and Completely Dyadic db-4 Wavelet Filter Bank -- Design of Dyadic Gabor Wavelet Filter Banks -- Design of Adaptive Gabor Wavelet Filter Banks.

Sommario/riassunto

Medical imaging is fundamental to modern healthcare, and its widespread use has resulted in creation of image databases. These repositories contain images from a diverse range of modalities, multidimensional as well as co-aligned multimodality images. These image collections offer opportunity for evidence-based diagnosis, teaching, and research. Advances in medical image analysis over last two decades shows there are now many algorithms and ideas available that allow to address medical image analysis tasks in commercial solutions with sufficient performance in terms of accuracy, reliability and speed. Content-based image retrieval (CBIR) is an image search technique that complements the conventional text-based retrieval of



images by using visual features, such as color, texture, and shape, as search criteria. This book emphasizes the design of wavelet filter-banks as efficient and effective feature descriptors for medical image retrieval. Firstly, a generalized novel design of a family of multiplier-free orthogonal wavelet filter-banks is presented. In this, the dyadic filter coefficients are obtained based on double-shifting orthogonality property with allowable deviation from original filter coefficients. Next, a low complex symmetric Daub-4 orthogonal wavelet filter-bank is presented. This is achieved by slightly altering the perfect reconstruction condition to make designed filter-bank symmetric and to obtain dyadic filter coefficients. In third contribution, the first dyadic Gabor wavelet filter-bank is presented based on slight alteration in orientation parameter without disturbing remaining Gabor wavelet parameters. In addition, a novel feature descriptor based on the design of adaptive Gabor wavelet filter-bank is presented. The use of Maximum likelihood estimation is suggested to measure the similarity between the feature vectors of heterogeneous medical images. The performance of the suggested methods is evaluated on three different publicly available databases namely NEMA, OASIS and EXACT09. The performance in terms of average retrieval precision, average retrieval recall and computational time are compared with well-known existing methods.