Deep Learning Models for Medical Imaging

Deep Learning Models for Medical Imaging

Santosh, K.C.
Das, Nibaran
Ghosh, Swarnendu

94,05 €(IVA inc.)

Deep Learning is a significant methodology in medical image analysis. Deep Learning Models for Medical Imaging presents deep learning concepts and modeling as applied to medical imaging and/or healthcare, using two different real-world case studies. It provides a complete implementation (via GitHub) of both standard (e.g. LeNet, Alexnet, VGGNet, ResNet and InceptionNet) and recent models (Mobile net and squeeze-and excitation net). Deep Learning Models for Medical Imaging is suitable for computer science, medical imaging and biomedical engineering researchers and students who need up-to-date deep learning tools to apply to medical image analysis problems. Provides a step-by-step approach to develop deep learning modelsPresents case studies showing end to end implementationCodes are provided in GitHub INDICE: 1. Introduction2. Deep learning: A review3. Deep learning models4. Case study I: Histopathology images5. Case study II: Chest radiographs6. Other medical imaging issues7. Conclusion

  • ISBN: 978-0-12-823504-1
  • Editorial: Academic Press
  • Encuadernacion: Rústica
  • Páginas: 180
  • Fecha Publicación: 01/06/2021
  • Nº Volúmenes: 1
  • Idioma: Inglés