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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Gans for Data Augmentation in Healthcare

Gans for Data Augmentation in Healthcare

Solanki, Arun
Naved, Mohd

Hardcover

Medical ReferenceTechnology & EngineeringGeneral Computers

ISBN10: 3031432045
ISBN13: 9783031432040
Publisher: Springer
Published: Nov 14 2023
Pages: 251
Weight: 1.20
Height: 0.63 Width: 6.14 Depth: 9.21
Language: English

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.

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