Organic thin-film transistor (OTFT) is a promising device technology for flexible large-area high-channel-count active-matrix neurostimulation system due to its flexibility and biocompatibility. However, circuits made by OTFT might be sensitive to device variation. As a result, it is difficult to achieve precise neurostimulation without any compensation structure in the pixel circuits. This work proposes a 6T2C threshold voltage compensation circuit for neurostimulation, which has low output current variation of 10.53%, reduced from the variation of 17.85% without compensation. We also improve the OTFT fabrication process with encapsulation to allow the circuits to operate under an electrolyte environment. Using the pixel circuits, we implement a 256-channel active-matrix neurostimulation system. The system can output stimulation with any pattern and allow each channel to output independently and simultaneously.

Implantable neuroprostheses require stimulators with high channel counts and mechanical flexibility. Organic thin-film transistor (OTFT), an essential building block for flexible circuits and system, is a promising candidate. However, the development of photolithographic OTFTs for complete bioelectronic system integration remains a challenge, due to their limited yield and uniformity. This paper reports a 4-mask photolithographic OTFT circuit integration technology, which shows a high device yield of 100% (50/50) and small device variation in threshold voltage of 0.64 V and in mobility of 4.9%. Using a device-circuit-system co-design approach, we demonstrate an active-matrix neurostimulation array comprised of 1024 pixels of a 4T1C stimulation circuits, in which independent stimulation intensity levels can be programmed and current stimulus at all channels can output simultaneously. The electrical function of the complete neurostimulation system is verified, showing a small variation of 15.59% for the output stimulation currents among pixels. This OTFT-based neurostimulation system provides a potential solution for the next-generation neurostimulators with high channel counts and mechanical flexibility.

In MRI-guided laser interstitial thermotherapy (MRgLITT), a signal void sometimes appears at the heating center of the measured temperature map. In neurosurgical MRgLITT treatments, cerebrospinal fluid pulsation (CSF), which may lead to temperature artifacts, also needs to be carefully managed. We find that signal loss in MR magnitude images can be one distinct contributor to the temperature imaging signal void. Therefore, this study aims to investigate this finding and more importantly. Also, this study intends to improve measurement accuracy by correcting CSF-induced temperature errors and employing a more reliable phase unwrapping algorithm. A gradient echo sequence with certain TE values for temperature imaging is used to quantify T2* variations during MRgLITT and to investigate the development of signal voids throughout the treatment. Informed by these findings, a multi-echo GRE sequence with appropriate TE coverage is employed. A multi-echo-based correction algorithm is developed to address the signal loss-induced temperature errors. A new phase unwrapping method and a new CSF pulsation correction approach are developed for multi-echo signal processing. The temperature imaging method is evaluated by gel phantom, ex-vivo, and in-vivo LITT heating experiments. T2* shortening during heating can be one important cause of the temperate imaging signal voids and this demands the multi-echo acquisition with varied TE values. The proposed multi-echo-based method can effectively correct signal loss-induced temperature errors and raise temperature estimation precision. The multi-echo thermometry in the in-vivo experiments shows smoother hotspot boundaries, fewer artifacts, and improved thermometry reliability. In the in-vivo experiments, the ablation areas estimated from the multi-echo thermometry also show satisfactory agreement with those determined from post-ablation MR imaging.

The aim of the current study was to improve temperature‐monitoring precision using multiecho proton resonance frequency shift‐based thermometry with view‐sharing acceleration for MR‐guided laser interstitial thermal therapy (MRgLITT) on a 0.5‐T low‐field MR system. Both precision and speed of the temperature measurement for clinical MRgLITT treatments suffer at low field, due to reduced image signal‐to‐noise ratio (SNR), decreased temperature‐induced phase changes, and limited RF receiver channels. In this work, a bipolar multiecho gradient‐recalled echo sequence with a temperature‐to‐noise ratio optimal weighted echo combination is applied to improve the temperature precision. A view‐sharing–based approach is utilized to accelerate signal acquisitions while preserving image SNRs. The method was evaluated using ex vivo (pork and pig brain) LITT heating experiments and in vivo (human brain) nonheating experiments on a high‐performance 0.5‐T scanner. In terms of results, (1) after echo combination, multiecho thermometry (i.e., ~7.5–40.5 ms, 7 TEs) provides ~1.5–1.9 times higher temperature precision than the no echo combination case (i.e., TE7 = 40.5 ms) within the same readout bandwidth. Additionally, echo registration is necessary for the bipolar multiecho sequence; (2) for a threefold acceleration, the view‐sharing approach with variable‐density subsampling shows around 1.8 times lower temperature errors than the GRAPPA method. Particularly for view‐sharing, variable‐density subsampling performs better than Interleave subsampling; and (3) ex vivo heating and in vivo nonheating experiments demonstrated that the temperature accuracy was less than 0.5 °C and that the temperature precision was less than 0.6 °C using the proposed 0.5‐T thermometry. It was concluded that view‐sharing accelerated multiecho thermometry is a practical temperature measurement approach for MRgLITT at 0.5 T.

Legged robots can travel through complex scenes via dynamic foothold adaptation. However, it remains a challenging task to efficiently utilize the dynamics of robots in cluttered environments and to achieve efficient navigation. We present a novel hierarchical vision navigation system combining foothold adaptation policy with locomotion control of the quadruped robots. The high-level policy trains an end-to-end navigation policy, generating an optimal path to approach the target with obstacle avoidance. Meanwhile, the low-level policy trains the foothold adaptation network through auto-annotated supervised learning to adjust the locomotion controller and to provide more feasible foot placement. Extensive experiments in both simulation and the real world show that the system achieves efficient navigation against challenges in dynamic and cluttered environments without prior information.

This work reports a novel low-temperature poly-silicon thin-film-transistor-based pixel circuit for active-matrix neurostimulation. The pixel circuit consists of four transistors and one capacitor (4T1C) for programmable current-mode stimulation, which are designed for storing stimulation intensity information, simultaneously stimulating a large number of channels, and discharging stimulation electrodes. Due to the high mobility and low threshold voltages of the devices, the fabricated circuit occupies a pixel area of $200\times 200\,\,\mu \text{m}\,\,^{\mathrm{ 2}}$ , and delivers a stimulation current of $147 ~\mu \text{A}$ , sufficient to stimulate a neuron. The turn-on resistance of the fabricated transistor is below 6 $\text{k}\Omega $ , sufficient to be used as switches for bioelectronic applications. By employing a discharging switch transistor, the accumulated charges on the stimulation electrodes were released, and the electrode voltage was reduced to 0.08 V, thus mitigating corrosion. We demonstrated that two pixel circuits at different rows and columns can output stimuli simultaneously without a noticeable delay. This pixel circuit shows high potential to scale up as an active-matrix neurostimulation system with a high channel count.

颅内病变磁共振监控激光间质热消融(LITT)是一种微创手术治疗方法,与传统开颅手术相比具有并发症发生率低、手术创伤更小的特点.LITT是用激光发出的热量消融目标靶点病变组织.在磁共振监控LITT手术中,使用导航定位机器人微创置入光纤,将激光能量准确输送到消融靶点,利用磁共振实时监测,精准控制消融区域内的温度场变化,利用预测模型可视化消融区的覆盖情况,实时调整光纤的位置以及激光能量,从而选择性地消融病变组织.该技术可以避开颅内关键结构与重要功能区,获得准确的消融区覆盖,实现安全精准的适形消融.颅内病灶激光消融治疗具有良好的有效性和安全性,为颅内病变治疗提供了一种微创的新途径.

Organic thin film transistor is one of the most promising electronic device technologies for flexible and printed electronics, but device uniformity remains a challenge for large-scale integration circuit design. Despite the advances in semiconductor layers, the quality of dielectric layers is equally important. Parylene-C dielectric has good intrasample thickness uniformity, but demonstrates significant variation among samples fabricated at the same time, thus causing device non-uniformity. In this study, we present a two-dimensional (2D) sample rotation method using a Ferris wheel to improve the thickness uniformity of parylene-C dielectrics. The Ferris wheel averages the deposition rate of parylene-C dielectric on different samples over an identical spherical space, rather than over different horizontal planes by the conventional one-dimensional sample rotation with a rack. The dielectrics fabricated on different cabins of the Ferris wheel demonstrate better thickness uniformity than those fabricated on different floors of the rack, and thus better uniformity of transistors. Specifically, using the 2D rotation Ferris wheel, the coefficient of variation of dielectric thickness is lowered to 0.01 from 0.12 (which uses the conventional rack); the coefficients of variation for the on-state drain current, process transconductance parameter, and threshold voltage of the fabricated transistors are improved to 0.15, 0.16 and 0.08, from 0.33, 0.20 and 0.14, respectively. The improved device uniformity has the potential in complicated flexible circuit design for advanced applications such as edge intelligence.

高频重复经颅磁刺激(rTMS)范式中序列间隔(ITI)参数对神经生理作用的影响尚未被充分研究.探讨不同ITI高频rTMS刺激初级运动皮层对双侧运动区神经活动能量的影响.11名健康受试者参与ITI分别为25、50、100 s的真10 Hz rTMS及伪10 Hz rTMS,序列时长为5 s.在每次rTMS前后采集180 s闭目静息态脑电信号,分析rTMS前后双侧运动区总频段及delta、theta、alpha、beta、gamma1、gamma2各频段功率谱密度和其偏侧指数的变化.结果 表明,25 s ITI rTMS对刺激侧运动区各频段功率谱密度均没有显著影响(P＞0.05);50 s ITIrTMS使刺激侧theta和beta频段功率谱密度显著增加(P＜0.05,theta频段刺激前后(11.42±1.01)dB vs(12.19±1.10) dB),beta频段刺激前后(10.71±0.99) dB vs(11.20±0.88) dB);同时使gamma2频段功率谱密度显著降低(P＜0.05,刺激前后(4.94±0.97)dB vs(3.35±0.61)dB);100 s ITI rTMS使刺激侧theta、alpha和beta频段功率谱密度显著增加(P＜0.05,theta频段刺激前后(11.29±1.00)dB vs(12.17±1.10) dB,alpha频段刺激前后(16.17±1.20)dB vs(17.74±1.20) dB,beta频段刺激前后(10.55±0.88)dB vs(11.26±0.90) dB).rTMS诱发刺激对侧运动区各频段功率谱的变化与刺激侧运动区的变化基本相同.在实验中,rTMS均没有改变双侧运动区功率谱密度的偏侧指数(P＞0.05).研究结果表明,高频rTMS范式设置的ITI不同,对双侧运动区脑活动的影响不同,提示制定高频rTMS范式时,需慎重考虑ITI的设置.

目的 利用比格犬动物实验,探讨采用国产激光消融治疗系统(LS1)和激光消融微创治疗套件(LS—T1)行磁共振引导下激光间质内热疗的安全性和有效性.方法 健康比格犬15只,行3T磁共振引导下激光间质内热疗,功率8W时间50 s,消融过程中磁共振实时扫描监测消融区域温度,系统软件计算最大消融横截面面积.消融后行增强T1磁共振扫描,测量增强毁损灶最大横截面面积.实验结束2周后安乐死比格犬,测量切片最大消融横截面积.对比分析系统计算、术后3D增强T1及切片测量的最大消融横截面积.结果 15只比格犬实验后均正常存活,系统计算最大消融截面面积为115.8±9.9 mm2,增强T1显示最大消融截面面积为115.7±1.0mm2,激光消融2周后组织切片最大消融截面面积为112.7±9.5 mm2.系统计算最大横截面积与增强T1显示最大横截面积差异无统计学意义(P=0.91),系统计算最大横截面积与切片测量最大横截面积差异有统计学意义(P＜0.01),增强T1显示最大横截面积与切片测量最大横截面积之间差异有统计学意义(P＜0.01).结论 应用国产激光消融治疗系统行磁共振引导下激光热疗是安全有效的,系统计算消融面积与消融后增强T1显示消融面积无明显差异.

In order to calibrate the hand-eye transformation of the surgical robot and laser range finder (LRF),a calibration algorithm based on a planar template was designed.A mathematical model of the planar template had been given and the approach to address the equations had been derived.Aiming at the problems of the measurement error in a practical system,we proposed a new algorithm for selecting coplanar data.This algorithm can effectively eliminate considerable measurement error data to improve the calibration accuracy.Furthermore,three orthogonal planes were used to improve the calibration accuracy,in which a nonlinear optimization for hand-eye calibration was used.With the purpose of verifying the calibration precision,we used the LRF to measure some fixed points in different directions and a cuboid's surfaces.Experimental results indicated that the precision of a single planar template method was (1.37± 0.24) mm,and that of the three orthogonal planes method was (0.37±0.05) mm.Moreover,the mean FRE of threedimensional (3D) points was 0.24 mm and mean TRE was 0.26 mm.The maximum angle measurement error was 0.4 degree.Experimental results show that the method presented in this paper is effective with high accuracy and can meet the requirements of surgical robot precise location.

This study aimed to introduce a new stereoelectroencephalography (SEEG) system based on Leksell stereotactic frame (L-SEEG) as well as Neurotech operation planning software, and to investigate its safety, applicability, and reliability. L-SEEG, without the help of navigation, includes SEEG operation planning software (Neurotech), Leksell stereotactic frame, and corresponding surgical instruments. Neurotech operation planning software can be used to display three-dimensional images of the cortex and cortical vessels and to plan the intracranial electrode implantation. In 44 refractory epilepsy patients, 364 intracranial electrodes were implanted through the L-SEEG system, and the postoperative complications such as bleeding, cerebral spinal fluid (CSF) leakage, infection, and electrode-related problems were also investigated. All electrodes were implanted accurately as preoperatively planned shown by postoperative lamina computed tomography and preoperative lamina magnetic resonance imaging. There was no severe complication after intracranial electrode implantation through the L-SEEG system. There were no electrode-related problems, no CSF leakage and no infection after surgery. All the patients recovered favorably after SEEG electrode implantation, and only 1 patient had asymptomatic frontal lateral ventricle hematoma (3 mL). The L-SEEG system with Neurotech operation planning software can be used for safe, accurate, and reliable intracranial electrode implantation for SEEG.

To avoid intracranial hemorrhage during minimally invasive depth electrode insertion without craniotomy for epilepsy surgery, precise in vivo imaging of cortical vessel and relevant rendering methods are critical, and should be used in preoperative planning. In this study, a non-invasive phase contrast MR angiography (PC-MRA) method was chosen for cortical vessel imaging. After image pre-processing (registration and segmentation), three visualization methods were implemented to optimize the vessel imaging and brain tissue rendering for surgical planning. The processed results were evaluated by comparing with intraoperative photographs. The results showed occurrences of missing vessels between imaging and photos (18.3%, 6 cases), but these could be compensated by realistic sulci visualization methods. The results showed 3D texture mapping to be the most suitable cortex visualization method for use in surgical navigation. Based on the methods and evaluations, a new surgical planning system and criteria of usage were developed with input from the surgeons' experience using the prototype system. This system could greatly help reduce the risk of the intracranial hemorrhage during electrode insertion and also avoid potential risks caused by contrast agent injections for contrast enhanced MRA or CTA.

PURPOSE:To evaluate the performance of automatic segmentation of atherosclerotic plaque components using solely multicontrast 3D gradient echo (GRE) magnetic resonance imaging (MRI). MATERIALS AND METHODS:A total of 15 patients with a history of recent transient ischemic attacks or stroke underwent carotid vessel wall imaging bilaterally with a combination of 2D turbo spin echo (TSE) sequences and 3D GRE sequences. The TSE sequences included T1-weighted, T2-weighted, and contrast-enhanced T1-weighted scans. The 3D GRE sequences included time-of-flight (TOF), magnetization-prepared rapid gradient echo (MP-RAGE), and motion-sensitized driven equilibrium prepared rapid gradient echo (MERGE) scans. From these images, the previously developed morphology-enhanced probabilistic plaque segmentation (MEPPS) algorithm was retrained based solely on the 3D GRE sequences to segment necrotic core (NC), calcification (CA), and loose matrix (LM). Segmentation performance was assessed using a leave-one-out cross-validation approach via comparing the new 3D-MEPPS algorithm to the original MEPPS algorithm that was based on the traditional multicontrast protocol including 2D TSE and TOF sequences. RESULTS:Twenty arteries of 15 subjects were found to exhibit significant plaques within the coverage of all imaging sequences. For these arteries, between new and original MEPPS algorithms, the areas per slice exhibited correlation coefficients of 0.86 for NC, 0.99 for CA, and 0.80 for LM; no significant area bias was observed. CONCLUSION:The combination of 3D imaging sequences (TOF, MP-RAGE, and MERGE) can provide sufficient contrast to distinguish NC, CA, and LM. Automatic segmentation using 3D sequences and traditional multicontrast protocol produced highly similar results.

Surgical navigation system has been widely used by surgeons to improve alignment accuracy during Total Knee Arthroplasty (TKA). In this article, we present an image-free surgical navigation system for TKA with a more interactive and robust in-house developed Graphical User Interface (GUI). The navigation system has a more intuitive view and can trace surgical steps easily by saving surgery information data. System steps, feature of the interactive GUI, coordinate definition and osteotomy value/angle calculation method have been introduced. The stability and accuracy test are performed.

X. Zhao, N. Balu, W. Liu, J. Wang, H. Zhao, J. Xu, and C. Yuan Department of Biomedical Engineering & Center for Biomedical Imaging Research, School of Medicine, Tsinghua University, Beijing, China, People's Republic of, Department of Radiology, University of Washington, Seattle, WA, United States, Philips Research North America, Briarcliff Manor, NY, United States, Department of Radiology, Renji hospital, Shanghai Jiao Tong University, Shanghai, China, People's Republic of

Introduction: The ability to identify plaque components in atherosclerotic carotid arteries using MRI is well established [1] and is amenable to automatic segmentation with techniques such as Morphology-Enhanced Probabilistic Plaque Segmentation (MEPPS) [2]. Measurements of components, such as necrotic core (NC), calcification (CA) and loose matrix (LM) have enabled researchers to identify plaque features associated with cerebral ischemic outcomes [3] and changes in plaque composition with treatment [4]. To date, these studies have primarily relied on 2D spin echo imaging techniques, but recent advances have led to numerous 3D gradient echo imaging techniques for vessel wall MRI. These 3D techniques, including 3D Magnetization Prepared Rapid Gradient Echo (MP-RAGE) [5] and 3D MSDE Prepared Rapid Gradient Echo (3D-MERGE) [6], offer vastly superior through-plane resolution, signal-to-noise ratio advantages, and scan time efficiency. An interesting possibility that emerges is the identification of plaque components based solely on these 3D sequences, with resulting isotropic, high-resolution maps of plaque components. To evaluate the use of 3D gradient echo imaging techniques to identify plaque components, this investigation sought to compare performance of an automatic segmentation algorithm based on MEPPS using traditional 2D spin echo images versus 3D gradient echo images. Materials and Methods: Four subjects with advanced atherosclerosis were imaged on a 3T MR scanner (Philips Achieva) using both an established protocol [1] with 2D T1, T2, and Contrast-Enhanced (CE) T1 turbo spin echo (TSE) images and 3D gradient echo images consisting of time-of-flight (TOF), MP-RAGE and 3D-MERGE. The 2D images were acquired at 2 mm intervals with in-plane resolution of 0.625 mm, whereas the 3D images were acquired with isotropic voxel sizes of 0.7 mm (3D-MERGE) or 0.625×0.625×2 mm (MP-RAGE and TOF). Custom software (CASCADE [7]) was used to register corresponding locations from all 6 contrast weightings and interactively draw vessel boundaries. Then MEPPS was applied to the 2D T1, T2, CE-T1 and TOF images to identify NC, CA, and LM. MEPPS segments carotid plaque based on a histologically-validated probability model of morphological and MRI signal characteristics. The components were then mapped to the 3D images and used to retrain the probability model of MRI signal characteristics based solely on 3D weightings. After training, we used the new probability model for MEPPS to segment the 3D images at 0.3 mm intervals along the carotid artery. The results were compared to the original 2D segmentation and used to visualize the plaque distribution not only on axial plane, but also on coronal and sagittal planes. The area of each location was computed for each component. These measurements were compared between 2D and 3D contrast weightings. Bias was assessed by means of a paired t-test, with P<0.05 considered a significant level of bias. Agreement was assessed by Pearson’s correlation coefficient (R). The comparison of the presence or absence of each location was assessed by Cohen’s κ value. Results: 64 locations (4 subjects, 16 locations for each) were classified and compared between 2D and 3D contrast weightings. The compared component area results are summarized in Table 1. In general, the results show good agreement with correlation coefficients for most components around 0.9 and high κ values for CA and NC. Agreement was moderate for LM with R value 0.63 and κ value 0.32. Fibrous tissue represents remaining unclassified tissue, which was present in all slices and therefore preclude calculation of κ. Significant trends of bias were observed with the areas of CA, NC, and LM. The fibrous tissue was not significantly different between 2D and 3D weightings. Isotropic data was also generated on the 3D contrast weightings with the voxel size 0.27×0.27×0.30(mm). Segmentation and probability map generation were implemented on the isotropic data. Figure 1 shows the visualization of the probability map on axial, coronal and sagittal planes. Discussion and Conclusions: The results of this work show in principle that a protocol based on 3D gradient echo contrast weightings provides sufficient information to quantitatively characterize CA, NC, and LM in carotid atherosclerotic plaque. Although discrepancies in absolute size were noted, strong correlations and high κ values suggest that with proper training and adjustment, robust automated segmentation based on 3D gradient echo images is possible. Of course, this result must be replicated with a larger sample size, which may, in fact, improve the result as the distribution of components is more accurately characterized. LM may, however, remain challenging as it is best depicted on T2-weighted and CE images. Finally, this study did not seek to separate NC into lipid and hemorrhage (IPH) components, but given the sensitivity of MP-RAGE to IPH [5], this should be possible. Overall, the advantage of this approach is especially well represented by the 3D visualization results. The isotropic segmentation results permit visualization of plaque structure in arbitrarily reformatted cuts. References 1. Saam ATVB 2005; 25:234-9. 2. Liu MRM 2006; 55:659-68. 3. Takaya, Stroke 200637:818-23. 4. Underhill Am Heart J 2008;155:584.e1-8. 5. Ota Radiology 2010;254:551-63. 6. Balu MRM 2010; 7. Kerwin TMRI 2007;18:371-8. Table 1. Comparison of Classification Results between 2D and 3D Contrast Weightings

In this paper we present a surgery planning software of total knee replacement (TKR). It was established initially based on the open source package —Visualization Toolkit (VTK). The main innovative feature of this surgery planning system is that it could help the surgeon to choose correct size, orientation and position of the prosthetic components, in order to restore the correct alignment of the mechanical axis of the lower limb. To simulate the multiple degrees of freedom of the embedded prosthesis in operation, such as introversion-extroversion, exterior-interior rotation, flexionextension, and translations along anatomical axes, in total knee replacement procedure, the appropriate human-machine interactive technology and alignment restrictions were designed to help the operator to perform the virtual cutting and virtual assembly manipulation. Moreover, the clinical commonly used quantitative index contradistinction was provided to assist the doctor to determine the spatial relation of the implantable prosthetic components in 3D space. The function design of the software system was evaluated by the virtual motion analysis of the knee flexion, which obtained a good effect. The process diagram and detailed treatments of virtual operation was provided in this paper. The software of surgery planning plays important roles in preoperative lectotype of the prosthesis and alignment procedure of bone resection and assembly operation.

Objective The identification of lower limb axes plays an important role in the kinematics research and clinical operation of total knee replacement surgery.This paper presents a method to extract the femoral axes based on CT images automatically.Method Using a series of image pre-processing algorithms such as segmentation,smoothing and rotations of the images,to get the 3-D fine mesh of lower limb bones.Then,by analyzing the morphological feature of 3-D femoral surface and based on the definitions of femoral mechanic axis and femoral anatomical axis,three feature points located on femoral head,femoral distal intercondylar notch and femoral shaft centre are selected to define the mechanical and anatomical axes of femur.In the light of the morphological feature of femur head,the center of femoral head was decided according to the changes of the gradient between each cross section of the femoral head.Meanwhile,we got the center of femoral intercondylar notch by calculating the closed-loop zone of cross sections of the bone.Those two points could finally define the mechanical axis of the femur.Result Based on a series of image processing procedures,three dimensional(3-D)surface model of lower limb bone were generated.By analyzing the morphological features of femoral head and knee joint center,a simple and convenient way was proposed to extract the coordinate of three feature points and further the femoral axes automatically.Conclusions Experimental results show that this processing procedure can extract the femoral mechanic axis and femoral anatomical axis precisely with 3-D CT images.

Image Guided Surgery (IGS) has been widely used in neurosurgical procedures to minimize invasion and to improve surgical accuracy. Registration is a key step of IGS, while Fiducial Localization Error (FLE) is an important factor affecting registration accuracy. FLE can be caused in both image domain (I-FLE) and physical domain (P-FLE). In this study, we design experiments to measure and compare the affecting factors on image FLE of point-based registration with special designed phantom. The results show that two factors affecting I-FLE are artificial picking and image voxel size. The artificial picking may cause the I-FLE average from 0.43 +/- 0.14mm to 0.74 +/- 0.26mm, and the voxel size may cause from 0.43 +/- 0.14 mm to 0.77 +/- 0.23 mm. The artificial picking error can be reduced by improving the picking person's experience, and we strongly recommend using smallest pixel spacing images for the registration. As for the selection of slice thickness, we find that the situation of Over-Sampling and Under-Sampling may occur, which would cause the thinner slice group of the image to get a higher I-FLE.