Deep learning-based methods, in particular, convolutional neural networks and fully
convolutional networks are now widely used in the medical image analysis domain. The …

Segmentation of the liver and tumours from computed tomography (CT) scans is an
important task in hepatic surgical planning. Manual segmentation of the liver and tumours is …

The human liver exhibits variable characteristics and anatomical information, which is often
ambiguous in radiological images. Machine learning can be of great assistance in …

Planning for palliative radiotherapy is performed without the advantage of MR or PET
imaging in many clinics. Here, we investigated CT-only GTV delineation for palliative …

Purpose: This paper proposes a new network framework called EAR-U-Net, which
leverages EfficientNetB4, attention gate, and residual learning techniques to achieve …

One of the traditionally used methods for segmenting images is by using a convolutional
neural network (CNN). CNN is helpful in various applications like object detection, image …