Advances in technology have been able to affect all aspects of human life. For example, the
use of technology in medicine has made significant contributions to human society. In this …

Segmentation of key brain tissues from 3D medical images is of great significance for brain
disease diagnosis, progression assessment and monitoring of neurologic conditions. While …

The Hausdorff Distance (HD) is widely used in evaluating medical image segmentation
methods. However, the existing segmentation methods do not attempt to reduce HD directly …

Manual image segmentation is a time-consuming task routinely performed in radiotherapy to
identify each patient's targets and anatomical structures. The efficacy and safety of the …

Rationale and Objectives The automated segmentation of organs and tissues throughout the
body using computed tomography and magnetic resonance imaging has been rapidly …

Aiming at the problem of low accuracy of traditional brain tumor detection, in this paper, a
combination of multimodal information fusion and convolution neural network detection …

Recently deep residual learning with residual units for training very deep neural networks
advanced the state-of-the-art performance on 2D image recognition tasks, eg, object …

Abstract Machine learning systems are achieving better performances at the cost of
becoming increasingly complex. However, because of that, they become less interpretable …

Background Computer-aided diagnosis (CAD) can assist physicians in effective and efficient
diagnostic decision-making. CAD systems are currently essential tools in some areas of …

Automatic 6-month infant brain tissue segmentation of magnetic resonance imaging (MRI) is
still less accurate owing to the low intensity contrast among tissues. To tackle the problem …