3D Head Pose Estimation Based On Graph Convolutional Network From A Single Rgb Image

Automatic localization of the biopsy needle in ultrasound images has become an important medical image analysis task, because it can directly translate to reducing the risk of damage to the tissues surrounding the lesion and spreading cancer cells. Although the algorithms to tackle this problem has been emerging at a steady pace, we lack a standardized way of validating them. in this paper, we tackle this issue and raise the attention of the research community to this experimental flaw which is especially important for the applications that can be ultimately deployed in the clinical settings. Our study, which involves a range of different training-test dataset splits performed over heterogeneous image data, showed that the incorrectly designed validation procedures can easily lead to overly optimistic conclusions concerning the abilities of such algorithms. We believe that our efforts will be an important step toward designing reproducible, rigorous, and fair approach for confronting the needle localization techniques in an unbiased way.