Name: Deep Learning in Medical Image Processing and Analysis (Healthcare Technologies) (en Inglés)
SKU: 55700697
Price: 148.61 USD
Availability: InStock
Author: Rabie Khaled,Karthik Chandran,Chowdhury Subrata

portada Deep Learning in Medical Image Processing and Analysis (Healthcare Technologies) (en Inglés)

Deep Learning in Medical Image Processing and Analysis (Healthcare Technologies) (en Inglés)

Formato

Libro Físico

Editorial

Institution Of Engineering & T

Autor

Rabie Khaled,Karthik Chandran,Chowdhury Subrata

Idioma

Inglés

N° páginas

374

Encuadernación

Tapa Dura

ISBN13

9781839537936

Deep Learning in Medical Image Processing and Analysis (Healthcare Technologies) (en Inglés)

Rabie Khaled,Karthik Chandran,Chowdhury Subrata (Autor) · Institution Of Engineering & T · Tapa Dura

Libro Nuevo Importado

Envío: 20 a 27 días háb.

$ 297.22$ 148.61

-50%

Costos de importación incluídos en el precio ✅

Libro Nuevo

Quedan más de 100 unidades

$ 148.61

Llega entre el 17 Sep y el 30 Sep a Quito, Pichincha. Seleccionar ubicación

Agregar a lista de deseos

Reseña del libro "Deep Learning in Medical Image Processing and Analysis (Healthcare Technologies) (en Inglés)"

Medical images, in various formats, are used by clinicians to identify abnormalities or markers associated with certain conditions, such as cancers, diseases, abnormalities or other adverse health conditions. Deep learning algorithms use vast volumes of data to train the computer to recognise certain features in the images that are associated with the disease or condition that you wish to identify. Whilst analysing the images by eye can take a lot of time, deep learning algorithms have the benefit of reviewing medical images at a faster rate than a human can, which aids the clinician, speeding up diagnoses and freeing up clinicians' time for other duties. Deep Learning in Medical Image Processing and Analysis introduces the fundamentals of deep learning for biomedical image analysis for applications including ophthalmology, cancer detection and heart disease. The book considers the principles of multi-instance feature selection, swarm optimisation, parallel processing models, artificial neural networks, support vector machines, as well as their design and optimisation, in biomedical applications. Topics such as data security, patient confidentiality, effectiveness and reliability will also be discussed. Written by an international team of experts, this edited book covers principles and applications for industry and academic researchers, scientists, engineers, developers, and designers in the fields of machine learning, deep learning, AI, image processing, signal processing, computer science or related fields. It will also be of interest to standards bodies and regulators, and clinicians using deep learning models.