商品描述
Computer-Assisted Diagnostics (CAD) using Convolutional Neural Network (CNN) model has become an important technology in the medical industry, improving the accuracy of diagnostics. However, the lack Magnetic Resonance Imaging (MRI) data leads to the failure of the depth study algorithm. Medical records often different because of the cost of obtaining information and the time-consuming information. In general, clinical data are unreliable, the training of neural network methods to distribute disease across classes does not yield the desired results. Data augmentation is often done by training data to solve problems caused by augmentation tasks such as scaling, cropping, flipping, padding, rotation, translation, affine transformation, and color augmentation techniques such as brightness, contrast, saturation, and hue.Data Augmentation and Segmentation imaging using GAN can be used to provide clear images of brain, liver, chest, abdomen, and liver on MRI. In addition, GAN shows strong promise in the field of clinical image synthesis. In many cases, clinical evaluation is limited by a lack of data and/or the cost of actual information. GAN can overcome these problems by enabling scientists and clinicians to work on beautiful and realistic images. This can improve diagnosis, prognosis, and disease. Finally, GAN highlights the potential for location of patient information with data. This is a beneficial clinical application of GAN because it can effectively protect patient confidentiality. The proposed book covers the application of GANs on medical imaging augmentation and segmentation.
商品描述(中文翻譯)
使用卷積神經網絡（Convolutional Neural Network, CNN）模型的電腦輔助診斷（Computer-Assisted Diagnostics, CAD）已成為醫療行業中的一項重要技術，提升了診斷的準確性。然而，缺乏磁共振成像（Magnetic Resonance Imaging, MRI）數據導致深度學習算法的失敗。由於獲取信息的成本和耗時，醫療記錄往往存在差異。一般而言，臨床數據不可靠，神經網絡方法在疾病分類上的訓練未能產生預期的結果。數據增強通常通過訓練數據來解決由於增強任務（如縮放、裁剪、翻轉、填充、旋轉、平移、仿射變換）以及顏色增強技術（如亮度、對比度、飽和度和色相）所引起的問題。使用生成對抗網絡（Generative Adversarial Network, GAN）進行數據增強和分割成像可以提供清晰的腦部、肝臟、胸部、腹部和肝臟的MRI影像。此外，GAN在臨床影像合成領域顯示出強大的潛力。在許多情況下，臨床評估受到數據不足和/或實際信息成本的限制。GAN可以通過使科學家和臨床醫生能夠處理美觀且真實的影像來克服這些問題。這可以改善診斷、預後和疾病管理。最後，GAN突顯了利用數據定位患者信息的潛力。這是GAN的一個有益臨床應用，因為它可以有效保護患者的隱私。所提議的書籍涵蓋了GAN在醫療影像增強和分割中的應用。
作者簡介
Dr. Arun Solanki is working as Assistant Professor in the Department of Computer Science and Engineering, Gautam Buddha University, Greater Noida, India where he has been working since 2009. He has worked as Time Table Coordinator, member Examination, Admission, Sports Council, Digital Information Cell, and other university teams from time to time. He has received M.Tech. Degree in Computer Engineering from YMCA University, Faridabad, Haryana, India. He has received his Ph.D. in Computer Science and Engineering from Gautam Buddha University in 2014. He has supervised more than 80 M.Tech. dissertations under his guidance.His research interests span Expert System, Machine Learning, and Search Engines. He has published many research articles in SCI/ Scopus indexed International journals/conferences like IEEE, Elsevier, Springer, etc. He has participated in many international conferences. He has been a technical and advisory committee member of many conferences. He has organized several FDP, Conferences, Workshops, and Seminars. He has chaired many sessions at International Conferences. Arun Solanki is working as Associate Editor in International Journal of Web-Based Learning and Teaching Technologies (IJWLTT)" IGI publisher. He has been working as Guest Editor for special issues in Recent Patents on Computer Science, Bentham Science Publishers. Arun Solanki is the editor of many Books with a reputed publisher like IGI Global, CRC and AAP. He is working as the reviewer in Springer, IGI Global, Elsevier, and other reputed publisher journals.Dr. Mohd Naved is a distinguished Associate Professor with an impressive career spanning over a decade in the fields of Business Analytics, Data Science, and Artificial Intelligence. As an educator, Dr. Naved has consistently demonstrated a commitment to the highest standards of teaching and mentoring, ensuring that his students receive an education that is both cutting-edge and grounded in real-world experience.His dedication to helping students achieve their full potential extends beyond the classroom, as he has been an active participant in the university's Mentor-Mentee Program, providing guidance and support to over 150 undergraduate and postgraduate students. In addition to his teaching prowess, Dr. Naved has excelled in the areas of education management, research, and curriculum development. He has served on various committees and led initiatives related to curriculum development, faculty recruitment and retention, and accreditation, contributing to the institutions he has worked with becoming centers of academic excellence in their respective fields. He has also successfully led the launch of several BBA/MBA programs, resulting in increased admissions and student satisfaction.As a researcher, Dr. Naved has made significant contributions to the fields of Business Analytics, Data Science, and Artificial Intelligence, with over 80+ publications in reputed scholarly journals andbooks. His research focuses on the applications of these disciplines in various industries, and he has supervised numerous research projects and dissertations, guiding students to successful outcomes.
作者簡介(中文翻譯)
阿倫·索蘭基博士目前擔任印度大諾伊達的高達姆·布達大學計算機科學與工程系的助理教授，自2009年以來一直在該校工作。他曾擔任課程表協調員、考試委員會成員、招生委員會成員、體育委員會成員、數位資訊中心成員及其他大學團隊的成員。他獲得了印度哈里亞納邦法里達巴德的YMCA大學計算機工程碩士學位，並於2014年在高達姆·布達大學獲得計算機科學與工程的博士學位。在他的指導下，他已經監督了超過80篇碩士論文。他的研究興趣涵蓋專家系統、機器學習和搜尋引擎。他在SCI/Scopus索引的國際期刊和會議上發表了許多研究文章，如IEEE、Elsevier、Springer等。他參加了多個國際會議，並擔任多個會議的技術和諮詢委員會成員。他組織了多個教學發展計畫、會議、工作坊和研討會，並在國際會議上主持了多個會議場次。阿倫·索蘭基擔任《國際網路學習與教學技術期刊》（IJWLTT）的副編輯，該期刊由IGI出版社出版。他還擔任《計算機科學近期專利》特刊的客座編輯，該期刊由Bentham Science Publishers出版。阿倫·索蘭基是多本由知名出版社如IGI Global、CRC和AAP出版的書籍的編輯。他在Springer、IGI Global、Elsevier及其他知名出版社的期刊中擔任審稿人。
穆罕默德·納維德博士是一位傑出的副教授，在商業分析、數據科學和人工智慧領域擁有超過十年的卓越職業生涯。作為一名教育工作者，納維德博士始終展現出對最高教學和輔導標準的承諾，確保他的學生接受到前沿且根植於實際經驗的教育。他對幫助學生實現潛力的奉獻精神超越了課堂，積極參與大學的導師-學員計畫，為超過150名本科生和研究生提供指導和支持。除了教學能力外，納維德博士在教育管理、研究和課程開發方面也表現出色。他曾在多個委員會任職，並主導與課程開發、教職員招聘與留任及認證相關的倡議，為他所任職的機構成為各自領域的學術卓越中心做出了貢獻。他還成功推動了多個BBA/MBA課程的推出，從而提高了招生數量和學生滿意度。作為一名研究者，納維德博士在商業分析、數據科學和人工智慧領域做出了重要貢獻，擁有超過80篇在知名學術期刊和書籍上發表的論文。他的研究專注於這些學科在各行各業的應用，並監督了多個研究項目和論文，指導學生取得成功的成果。
