Feature Extraction in Medical Image Retrieval: A New Design of Wavelet Filter Banks (醫學影像檢索中的特徵提取：小波濾波器組的新設計)

Samantaray, Aswini Kumar, Rahulkar, Amol D.

Feature Extraction in Medical Image Retrieval: A New Design of Wavelet Filter Banks
  • 出版商: Springer
  • 出版日期: 2024-05-16
  • 售價: $6,660
  • 貴賓價: 9.5 折 $6,327
  • 語言: 英文
  • 頁數: 155
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 3031572785
  • ISBN-13: 9783031572784

    • 海外代購書籍(需單獨結帳)

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商品描述

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.

商品描述(中文翻譯)

醫學影像對現代醫療保健至關重要，其廣泛使用導致了影像資料庫的建立。這些資料庫包含來自多種影像模式的影像，包括多維影像以及協調對齊的多模態影像。這些影像集合為基於證據的診斷、教學和研究提供了機會。在過去二十年中，醫學影像分析的進展顯示，現在有許多算法和理念可用於商業解決方案中的醫學影像分析任務，並在準確性、可靠性和速度方面具備足夠的性能。基於內容的影像檢索（CBIR）是一種影像搜尋技術，通過使用視覺特徵（如顏色、紋理和形狀）作為搜尋標準，來補充傳統的基於文本的影像檢索。本書強調將小波濾波器組設計為醫學影像檢索的高效且有效的特徵描述子。

首先，提出了一種無乘法器的正交小波濾波器組的通用新設計。在此設計中，二元濾波器係數是基於雙重移位正交性質獲得的，並允許與原始濾波器係數有一定的偏差。接下來，介紹了一種低複雜度的對稱 Daub-4 正交小波濾波器組。這是通過稍微改變完美重建條件來實現的，以使設計的濾波器組對稱並獲得二元濾波器係數。在第三項貢獻中，提出了第一個基於輕微改變方向參數的二元 Gabor 小波濾波器組，而不干擾其餘的 Gabor 小波參數。此外，還提出了一種基於自適應 Gabor 小波濾波器組設計的新型特徵描述子。建議使用最大似然估計來測量異質醫學影像特徵向量之間的相似性。所提出方法的性能在三個不同的公開資料庫上進行評估，分別為 NEMA、OASIS 和 EXACT09。在平均檢索精度、平均檢索召回率和計算時間方面，與現有的知名方法進行比較。

作者簡介

Dr. Aswini Kumar Samantaray received his B.Tech. and M.Tech. degree in electronics and communication engineering from Biju Patanaik University of Technology, Odisha, India in 2008 and 2012 respectively. He received his Ph.D. degree from National Institute of Technology Goa (NIT Goa), India in 2022. He worked as an Assistant Professor with the C. V. Raman College of Engineering from 2008 to 2018. He is currently working as an assistant professor with electronics and communication engineering, Vignan's Foundation for Science, Tecchnology and Research, Guntur, India. His research interests include the design of wavelets and filter-banks, image processing, and FPGA accelerators.

Dr. Amol D. Rahulkar received the B.E. degree in instrumentation engineering from the Shri Guru Gobind Singhji (SGGS) Institute of Engineering and Technology, Nanded, India, in 2000, the M.Tech. degree from the Indian Institute of Technology (IIT) Kharagpur, India, in 2002, and the Ph.D. degree from the SGGS Institute of Engineering and Technology, Nanded, affiliated to Swami Ramanand Teerth Marathwada University Nanded, India, in 2013. He is currently working as an Associate Professor with the Department of Electrical and Electronics Engineering, National Institute of Technology Goa (NIT Goa), India. His current research interests include the design of wavelets and filter-banks, digital signal processing, image processing, biometrics, FPGA accelerators, and soft-computing.

作者簡介(中文翻譯)

阿斯維尼·庫馬·薩曼塔雷博士於2008年和2012年分別在印度奧迪沙的比朱·帕塔奈克科技大學獲得電子與通信工程的學士和碩士學位。他於2022年在印度國立科技學院果阿分校（NIT Goa）獲得博士學位。他曾於2008年至2018年擔任C.V.拉曼工程學院的助理教授。目前，他在印度甘土爾的維根科技研究基金會擔任電子與通信工程的助理教授。他的研究興趣包括小波和濾波器組的設計、影像處理以及FPGA加速器。

阿莫爾·D·拉胡爾卡博士於2000年在印度南德的施里·古魯·戈賓德·辛格吉工程與技術學院獲得儀器工程的學士學位，於2002年在印度卡拉格普爾的印度理工學院（IIT）獲得碩士學位，並於2013年在南德的SGGS工程與技術學院獲得博士學位，該學院隸屬於斯瓦米·拉馬南德·提爾特·馬拉特瓦達大學。現在，他在印度國立科技學院果阿分校（NIT Goa）的電氣與電子工程系擔任副教授。他目前的研究興趣包括小波和濾波器組的設計、數位信號處理、影像處理、生物識別、FPGA加速器和軟計算。

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