CaraNet: Context Axial Reverse Attention Network for Segmentation of Small Medical Objects

Understand

Segmenting medical images accurately and reliably is important for disease diagnosis and treatment.

• It is a challenging task because of the wide variety of objects' sizes, shapes, and scanning modalities.
• Recently, many convolutional neural networks (CNN) have been designed for segmentation tasks and achieved great success.
• Few studies, however, have fully considered the sizes of objects, and thus most demonstrate poor performance for small objects segmentation.