Abstract: Image segmentation ... of active learning methods still require huge computational costs and utilize unlabeled data inefficiently. They also tend to ignore the intermediate knowledge within ...

In this paper, we propose a waste segmentation method using Convolutional Neural Network based on the Encoder-Decoder approach of SegNet architecture [5]. We compare two different setups of the ...

The selection of sub-volumes for the pelvic bone sites therefore requires expert knowledge to determine the first and last image for each bone site ... Figure 2. Deep learning (DL) segmentation ...

This study developed CMF-ELSeg, a novel fully automatic multi-structure segmentation model based on deep ensemble learning. Methods: A total of 143 CMF computed tomography (CT) scans were ...

aArtificial Intelligence in Medicine Program, Mass General Brigham, Harvard Medical School, Boston, MA, USA bDepartment of Radiation Oncology, Brigham and Women’s Hospital, Dana-Farber Cancer ...