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Delineating the lesion area is an important task in image-based diagnosis.Pixel-wise classification is a popular approach to segmenting the region ofinterest. However, at fuzzy boundaries such methods usually result in glitches,discontinuity, or disconnection, inconsistent with the fact that lesions aresolid and smooth. To overcome these undesirable artifacts, we propose theBezierSeg model which outputs bezier curves encompassing the region ofinterest. Directly modelling the contour with analytic equations ensures thatthe segmentation is connected, continuous, and the boundary is smooth. Inaddition, it offers sub-pixel accuracy. Without loss of accuracy, the beziercontour can be resampled and overlaid with images of any resolution. Moreover,a doctor can conveniently adjust the curve's control points to refine theresult. Our experiments show that the proposed method runs in real time andachieves accuracy competitive with pixel-wise segmentation models.

BezierSeg: Parametric Shape Representation for Fast Object Segmentation in Medical Images