1.

Record Nr.

UNINA9910464583703321

Titolo

Nanoscale nonlinear PANDA ring resonator / / Preecha P. Yupapin. [et al.]

Pubbl/distr/stampa

Enfield, N.H. : , : Science Publishers

Boca Raton, Fla. : , : Distributed by CRC Press, , 2012

ISBN

0-429-08616-4

1-4398-9391-8

Descrizione fisica

1 online resource (310 p.)

Altri autori (Persone)

YupapinPreecha P

Disciplina

621.36/93

Soggetti

Integrated optics

Optical resonance

Resonators

Nonlinear waves

Nanoelectronics

Electronic books.

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references at the end of each chapters.

Nota di contenuto

Front Cover; Preface; Contents; 1. Linear and Nonlinear Ring Resonators; 2. A PANDA Ring Resonator; 3. Dark-Bright Soliton Conversion; 4. Dynamic Optical Tweezers; 5. Hybrid Interferometer; 6. Hybrid Transceiver; 7. Nanocommunication; 8. Nanosensors; 9. Optical and Quantum Computing; 10. Drug Delivery; 11. Hybrid Transistor; 12. Electron-Hole Pair Manipulation

Sommario/riassunto

Microring/nanoring resonator is an interesting device that has been widely studied and investigated by researchers from a variety of specializations. This book begins with the basic background of linear and nonlinear ring resonators. A novel design of nano device known as a PANDA ring resonator is proposed. The use of the device in the form of a PANDA in applications such as nanoelectronics, measurement, communication, sensors, optical and quantum computing, drug delivery, hybrid transistor and a new concept of electron-hole pair is discussed in detail.



2.

Record Nr.

UNINA9910483740603321

Autore

Bhateja Vikrant

Titolo

Non-Linear Filters for Mammogram Enhancement : A Robust Computer-aided Analysis Framework for Early Detection of Breast Cancer / / by Vikrant Bhateja, Mukul Misra, Shabana Urooj

Pubbl/distr/stampa

Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2020

ISBN

981-15-0442-3

Edizione

[1st ed. 2020.]

Descrizione fisica

1 online resource (xxviii, 239 pages) : illustrations

Collana

Studies in Computational Intelligence, , 1860-9503 ; ; 861

Disciplina

618.1907572

Soggetti

Computational intelligence

Computer vision

Radiology

Cancer

Computational Intelligence

Computer Vision

Cancer Biology

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di bibliografia

Includes bibliographical references.

Nota di contenuto

Introduction: Computer-aided Analysis of Mammograms for Diagnosis of Breast Cancer -- Mammogram Enhancement: Background -- Methodology: Motivation, Objectives and Proposed Solution Approach -- Performance Evaluation and Benchmarking of Mammogram Enhancement Approaches: Mammographic Image Quality Assessment -- Non-linear Polynomial Filters: Overview, Evolution and Proposed Mathematical Formulation -- Non-linear Polynomial Filters for Contrast Enhancement of Mammograms -- Non-linear Polynomial Filters for Edge Enhancement of Mammograms -- Human Visual System Based Unsharp Masking for Enhancement of Mammograms -- Conclusions and Future Scope: Applications, Contributions and Impact.

Sommario/riassunto

This book presents non-linear image enhancement approaches to mammograms as a robust computer-aided analysis solution for the early detection of breast cancer, and provides a compendium of non-linear mammogram enhancement approaches: from the fundamentals to research challenges, practical implementations, validation, and



advances in applications. The book includes a comprehensive discussion on breast cancer, mammography, breast anomalies, and computer-aided analysis of mammograms. It also addresses fundamental concepts of mammogram enhancement and associated challenges, and features a detailed review of various state-of-the-art approaches to the enhancement of mammographic images and emerging research gaps. Given its scope, the book offers a valuable asset for radiologists and medical experts (oncologists), as mammogram visualization can enhance the precision of their diagnostic analyses; and for researchers and engineers, as the analysis of non-linear filters is one ofthe most challenging research domains in image processing. .