arXiv 2310.019872023-12-13eess.IV

用于对比存在内部病变的苹果果实的多张切片照片与CT扫描图像的2D到3D联合图像配准工作流

Joint 2D to 3D image registration workflow for comparing multiple slice photographs and CT scans of apple fruit with internal disorders

Dirk Elias Schut, Rachael Maree Wood, Anna Katharina Trull, Rob Schouten, Robert van Liere, Tristan van Leeuwen, Kees Joost Batenburg

备注：: 20 pages, 9 figures 13-Dec-2023 revision: The plan to make the paper part-one of a two-part series was cancelled. Therefore the title of this paper and the title in the reference to the part-two paper (Wood et al., 2023) were changed

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AI总结：

本研究提出一种2D到3D联合图像配准工作流，构建苹果切片照片与CT切片的对齐数据集，可用于研究苹果内部病变的CT检测，且经调整可拓展至其他水果或MRI场景。

摘要：

很大比例的苹果在长期贮藏后会出现内部病变，导致其无法进入供应链。CT成像是一种用于在线检测这些病变的极具潜力的技术。因此，明确不同病变如何影响CT扫描中可观测到的图像特征至关重要。本文提出了一种工作流，用于构建苹果切片照片与其对应CT切片的图像对数据集。通过获取苹果同一部位的CT图像和照片图像，可利用两种图像中的互补信息，研究内部病变的潜在形成过程，以及如何在CT图像中量化内部病变。该工作流涵盖数据采集、图像分割、图像配准和验证方法。图像配准方法在假设切片平行的前提下，将单个苹果的所有可用切片的配准纳入同一个优化问题中求解。该方法的表现优于对每个切片单独优化配准的方案。研究应用该工作流构建了包含1347组切片照片及其对应CT切片的数据集。该数据集采集自107个经气调（CA）贮藏8个月的‘Kanzi’苹果。在该数据集中，切片照片上的标注与匹配CT切片上的对应标注之间的平均距离为1.47±0.40 mm。我们的工作流能够采集大量精确对齐的照片-CT图像对数据集，有助于区分在CT上外观相似的内部病变。稍作修改后，类似的工作流还可应用于其他水果，或是替代CT扫描用于MRI成像。

英文摘要：

A large percentage of apples are affected by internal disorders after long-term storage, which makes them unacceptable in the supply chain. CT imaging is a promising technique for in-line detection of these disorders. Therefore, it is crucial to understand how different disorders affect the image features that can be observed in CT scans. This paper presents a workflow for creating datasets of image pairs of photographs of apple slices and their corresponding CT slices. By having CT and photographic images of the same part of the apple, the complementary information in both images can be used to study the processes underlying internal disorders and how internal disorders can be measured in CT images. The workflow includes data acquisition, image segmentation, image registration, and validation methods. The image registration method aligns all available slices of an apple within a single optimization problem, assuming that the slices are parallel. This method outperformed optimizing the alignment separately for each slice. The workflow was applied to create a dataset of 1347 slice photographs and their corresponding CT slices. The dataset was acquired from 107 'Kanzi' apples that had been stored in controlled atmosphere (CA) storage for 8 months. In this dataset, the distance between annotations in the slice photograph and the matching CT slice was, on average, $1.47 \pm 0.40$ mm. Our workflow allows collecting large datasets of accurately aligned photo-CT image pairs, which can help distinguish internal disorders with a similar appearance on CT. With slight modifications, a similar workflow can be applied to other fruits or MRI instead of CT scans.

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