将医学成像纤维束追踪技术应用于图像的绘画风格渲染 (Applying Medical Imaging Tractography Techniques to Painterly Rendering of Images)

from arxiv, Exploratory investigation applying medical imaging tractography techniques to painterly image rendering. Code available at https://github.com/tito21/st-python

Doctors and researchers routinely use diffusion tensor imaging (DTI) and tractography to visualize the fibrous structure of tissues in the human body. This paper explores the connection of these techniques to the painterly rendering of images. Using a tractography algorithm the presented method can place brush strokes that mimic the painting process of human artists, analogously to how fibres are tracked in DTI. The analogue to the diffusion tensor for image orientation is the structural tensor, which can provide better local orientation information than the gradient alone. I demonstrate this technique in portraits and general images, and discuss the parallels between fibre tracking and brush stroke placement, and frame it in the language of tractography. This work presents an exploratory investigation into the cross-domain application of diffusion tensor imaging techniques to painterly rendering of images. All the code is available at https://github.com/tito21/st-python

翻译：医生和研究人员常规使用扩散张量成像（DTI）与纤维束追踪技术来可视化人体组织的纤维结构。本文探讨了这些技术与图像绘画风格渲染之间的关联。通过采用纤维束追踪算法，所提出的方法能够放置模仿人类艺术家绘画过程的笔触，类似于DTI中追踪纤维的方式。在图像方向分析中，结构张量可类比于扩散张量，其能提供比单独梯度更优的局部方向信息。本文通过肖像与通用图像展示了该技术，并讨论了纤维追踪与笔触放置之间的相似性，同时以纤维束追踪的术语框架进行阐释。本工作探索性地研究了扩散张量成像技术在跨领域应用于图像绘画风格渲染的可行性。全部代码发布于 https://github.com/tito21/st-python