An Ensemble of Fine-Tuned Convolutional Neural Networks for Medical Image Classification
University of Sydney · Royal Prince Alfred Hospital · +1 more institution
Abstract
The availability of medical imaging data from clinical archives, research literature, and clinical manuals, coupled with recent advances in computer vision offer the opportunity for image-based diagnosis, teaching, and biomedical research. However, the content and semantics of an image can vary depending on its modality and as such the identification of image modality is an important preliminary step. The key challenge for automatically classifying the modality of a medical image is due to the visual characteristics of different modalities: some are visually distinct while others may have only subtle differences. This challenge is compounded by variations in the appearance of images based on the diseases…
Citation impact
- FWCI
- 52.12
- Percentile
- 100%
- References
- 57
Authors
5Topics & keywords
- Convolutional neural network
- Computer science
- Artificial intelligence
- Modality (human–computer interaction)
- Contextual image classification
- Pattern recognition (psychology)
- Feature (linguistics)
- Modalities