AI RESEARCH
KaLDeX: Kalman Filter based Linear Deformable Cross Attention for Retina Vessel Segmentation
arXiv CS.CV
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ArXi:2410.21160v2 Announce Type: replace-cross Background and Objective: In the realm of ophthalmic imaging, accurate vascular segmentation is paramount for diagnosing and managing various eye diseases. Contemporary deep learning-based vascular segmentation models rival human accuracy but still face substantial challenges in accurately segmenting minuscule blood vessels in neural network applications. Due to the necessity of multiple downsampling operations in the CNN models, fine details from high-resolution images are inevitably lost.