We propose an accurate clinical tool to simultaneously recognize vertebrae labels and bounding boxes from arbitrary input MRI images.

Oct 9, 2020 · Can-See is designed as a two-step detection framework: (1) A hierarchical proposal network (HPN) to perceive the existence of the vertebrae. HPN ...

Oct 10, 2019 · In this paper, we propose a Hierarchical Self-calibration Detection Framework (Hi-scene) to precisely recognize the labels and bounding boxes of ...

In this paper, we propose a Hierarchical Self-calibration Detection Framework (Hi-scene) to precisely recognize the labels and bounding boxes of all vertebrae ...

In this paper, we propose a Hierarchical Self-calibration Detection Framework (Hi-scene) to precisely recognize the labels and bounding boxes of all vertebrae ...

A Hierarchical Self-calibration Detection Framework (Hi-scene) to precisely recognize the labels and bounding boxes of all vertebrae in an arbitrary spine ...

Oct 9, 2020 · Can-See is designed as a two-step detection framework: (1) A hierarchical proposal network (HPN) to perceive the existence of the vertebrae. HPN ...

Automatic vertebrae recognition from arbitrary spine MRI images by a category-Consistent self-calibration detection framework.

Accurate vertebrae recognition is crucial in spinal disease localization and successive treatment planning. Although vertebrae detection has been studied ...

Automatic vertebra recognition has the potential to non-subjectively localize and label every vertebra from MRI images; thus, it may be beneficial for accurate ...