9783031432040 - gans for data augmentation in healthcare (13 resultados)
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Librería: Ria Christie Collections, Uxbridge, Reino UnidoRia Christie Collections
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Librería: Buchpark, Trebbin, AlemaniaBuchpark
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Condición: Hervorragend. Zustand: Hervorragend | Seiten: 264 | Sprache: Englisch | Produktart: Bücher | 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 are often different because of the cost of obtaining information and the time spent consuming the information. In general, clinical data is unreliable and therefore 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 an 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 within the data. This is a beneficial clinical application of GAN because it can effectivelyprotect patient confidentiality. This book covers the application of GANs on medical imaging augmentation and segmentation.
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Librería: Books Puddle, New York, NY, Estados Unidos de AmericaBooks Puddle
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EUR 224,48
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Condición: New. pp. 264.
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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
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EUR 171,19
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Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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 fail…ure of the depth study algorithm. Medical records are often different because of the cost of obtaining information and the time spent consuming the information. In general, clinical data is unreliable and therefore 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 an 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 within the data. This is a beneficial clinical application of GAN because it can effectivelyprotect patient confidentiality. This book covers the application of GANs on medical imaging augmentation and segmentation.
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Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
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EUR 249,46
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Hardcover. Condición: Brand New. 261 pages. 9.25x6.10x9.21 inches. In Stock.
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Librería: BUCHSERVICE / ANTIQUARIAT Lars Lutzer, Wahlstedt, AlemaniaBUCHSERVICE / ANTIQUARIAT Lars Lutzer
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Hardcover. Condición: gut. 2023. GANs for Data Augmentation in Healthcare In deutscher Sprache. pages.
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Librería: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
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Condición: new. Questo è un articolo print on demand.
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Librería: Basi6 International, Irving, TX, Estados Unidos de AmericaBasi6 International
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EUR 145,55
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Condición: Brand New. New. Delivery takes 20-25 days. Print on Demand.
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Librería: moluna, Greven, Alemaniamoluna
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EUR 144,94
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Gebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Oriented towards the applications and not just the theoryContains work from some of the pioneers of GANCovers practical aspects with possible supported resultsDr. Arun Solanki is working as Assistant Profess…or in the Department of C.
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.
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EUR 171,19
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Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 l…eads 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. This book covers the application of GANs on medical imaging augmentation and segmentation. 264 pp. Englisch.
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Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000
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EUR 171,19
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Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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 are often different because of the cost of obtaining information and the time spent consuming the information. In general, clinical data is unreliable and therefore 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 an 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 within the data. This is a beneficial clinical application of GAN because it can effectivelyprotect patient confidentiality. This book covers the application of GANs on medical imaging augmentation and segmentation.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 264 pp. Englisch.
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Librería: Majestic Books, Hounslow, Reino UnidoMajestic Books
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EUR 235,00
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Condición: New. Print on Demand pp. 264.
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Librería: Biblios, frankfurt am main, HESSE, AlemaniaBiblios
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EUR 239,21
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Condición: New. PRINT ON DEMAND pp. 264.
