Department of Internal Medicine and Allergology, Cantonal Hospital, Italian Hospital, Lugano, Switzerland
Mini Review
A overview of the use of multi-modality fusion and deep learning for medical picture segmentation
Author(s): Sadia Stefano*
Due to its ability to provide multiple information about a target
(tumor, organ, or tissue), multi-modality is frequently utilized
in medical imaging. In order to improve the segmentation,
multimodality segmentation involves fusing multiple information
sources. In recent times, approaches based on deep learning
have demonstrated cutting-edge results in image classification,
segmentation, object detection, and tracking tasks. Multi-modal
medical image segmentation has recently also piqued the interest
of deep learning researchers due to their capacity for self-learning
and generalization across large amounts of data. We present an
overview of deep learning-based methods for the multi-modal
medical image segmentation task in this paper. Multi-modal medical
image segmentation and the general principle of deep learning are
first discusse.. View More»
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