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After each robot end tool replacement, tool center point (TCP) calibration must be performed to achieve precise control of the end tool. This process is also essential for robot-assisted puncture surgery. The purpose of this article is to solve the problems of poor accuracy stability and strong operational dependence in traditional TCP calibration methods and to propose a TCP calibration method that is more suitable for a physician. This paper designs a special binocular vision system and proposes a vision-based TCP calibration algorithm that simultaneously identifies tool center point position (TCPP) and tool center point frame (TCPF). An accuracy test experiment proves that the designed special binocular system has a positioning accuracy of ±0.05 mm. Experimental research shows that the magnitude of the robot configuration set is a key factor affecting the accuracy of TCPP. Accuracy of TCPF is not sensitive to the robot configuration set. Comparison experiments show that the proposed TCP calibration method reduces the time consumption by 82%, improves the accuracy of TCPP by 65% and improves the accuracy of TCPF by 52% compared to the traditional method. Therefore, the method proposed in this article has higher accuracy, better stability, less time consumption and less dependence on the operations than traditional methods, which has a positive effect on the clinical application of high-precision robot-assisted puncture surgery.

A c c e p t e d M a n u s c r i p tWe developed an algorithm to estimate the thickness of cervical cytology specimens.The proposed algorithm reached an accuracy of 1 micron at 90% of times.The algorithm was used to quantitatively analysis of ten normal Thin-prep cervical cytology slides.It was found that the distribution of cells is skewed towards the cover-slip (top of the slide).It was also proved that considering the thickness of focal points produced focus maps in superior qualities compared to conventional ones. Highlights (for review)Page 2 of 28 A c c e p t e d M a n u s c r i p t AbstractKnowledge of the spatial distribution and thickness of cytology specimens is critical to the development of digital slide acquisition techniques that minimise both scan times and image file size. In this paper, we evaluate a novel method to achieve this goal utilising an exhaustive high-resolution scan, an over-complete wavelet transform across multi-focal planes and a clump segmentation of all cellular material on the slide. The method is demonstrated with a quantitative analysis of ten normal, but difficult to scan Pap stained, Thin-prep, cervical cytology slides. We show that with this method the top and bottom of the specimen can be estimated to an accuracy of 1 micron in 88% and 97% of the fields of view respectively. Overall, cellar material can be over 30 microns thick and the distribution of cells is skewed towards the cover-slip (top of the slide). However, the median clump thickness is 10 microns and only 31% of clumps contain more than three nuclei. Therefore, by finding a focal map of the specimen the number of 1 micron spaced focal planes that are required to be scanned to acquire 95% of the in-focus material can be reduced from 25.4 to 21.4 on average. In addition, we show that by considering the thickness of the specimen, an improved focal map can be produced which further reduces the required number of 1 micron spaced focal planes to 18.6. This has the potential to reduce scan times and raw image data by over 25%.

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