Manual Registration Research Articles

Sistem Informasi Pendaftaran untuk Kompetisi Airsoft Group dengan Metode Prototyping

The Airsoft Group Competition (ARGO) is an airsoft gun championship event held after the airsoft fan group Anarchy99 Magelang. The manual registration system in airsoft competition has many disadvantages, it requires time to search for participant data, it is prone to double participants that are not needed by the competition participants and if there are participants with the same name, it is difficult for one participant to another. The purpose of this study is to obtain a registration information system to facilitate participants and organizers in carrying out the registration process and making reports. With a large number of participants spread throughout Indonesia, this championship requires information systems. The method used in making this information system uses the prototype method. The results obtained from research testing with the Black Box Testing method and conducted on the user, can be concluded related to the system built has met the needs of the procurement of information systems that help the registration process and help the participant data and conduct purchase. Requires a long time in making reports.

3-D-Printed Registration Phantom for Combined Ultrasound and Optical Imaging of Biological Tissues

Efforts to develop quantitative ultrasound biomarkers would benefit from comparisons between ultrasound data and higher-resolution images of the tissue microstructure, such as from optical microscopy. However, only a few studies have used these methods for multiscale imaging because it is difficult to register low-resolution (>100 μm) ultrasound images to high-resolution microscopy images. To address this need, we have designed a 3-D-printed registration phantom that is made of a hard fluorescent resin, fits into a glass-bottom dish and can be used to calculate a coordinate system transform between ultrasound and optical microscopy. We report the phantom design, a registration protocol and an example registration using 18.5-MHz ultrasound and second harmonic generation microscopy. We evaluate the registration precision, achieving standard deviations smaller than the ultrasound resolution across all axes, and illustrate on a mouse mammary gland that this method yields results superior to those of manual landmark registration.

Machine learning application for incident prostate adenocarcinomas automatic registration in a French regional cancer registry

SummaryCancer registries are collections of curated data about malignant tumor diseases. The amount of data processed by cancer registries increases every year, making manual registration more and more tedious. ObjectiveWe sought to develop an automatic analysis pipeline that would be able to identify and preprocess registry input for incident prostate adenocarcinomas in a French regional cancer registry. MethodsNotifications from different sources submitted to the Bas-Rhin cancer registry were used here: pathology data and, ICD 10 diagnosis codes from hospital discharge data and healthcare insurance data. We trained a Support Vector Machine model (machine learning) to predict whether patient’s data must be considered or not as a prostate adenocarcinoma incident case that should therefore be registered. The final registration of all identified cases was manually confirmed by a specialized technician. Text mining tools (regular expressions) were used to extract clinical and biological data from non-structured pathology reports. ResultsWe performed two successive analyses. First, we used 982 cases manually labeled by registrars from the 2014 dataset to predict the registration of 785 cases submitted in 2015. Then, we repeated the procedure using the 2089 cases labeled by registrars from the 2014 and 2015 datasets to predict the registration of 926 cases submitted in the 2016 data. The algorithm identified 663 cases of prostate adenocarcinoma in 2015, and 610 in 2016. From these findings, 663 and 531 cases were respectively added to the registry; and 641 and 512 cases were confirmed by the specialized technician. This registration process has achieved a precision level above 96 %. The algorithm obtained an overall precision of 99 % (99.5 % in 2015 and 98.5 % in 2016) and a recall of 97 % (97.8 % in 2015 and 96.9 % in 2016). When the information was found in pathology report, text mining was more than 90 % accuracy for major indicators: PSA test, Gleason score, and incidence date). For both PSA and tumor side, information was not detected in the majority of cases.” ConclusionMachine learning was able to identify new cases of prostate cancer, and text mining was able to prefill the data about incident cases. Machine-learning-based automation of the registration process could reduce delays in data production and allow investigators to devote more time to complex tasks and analysis.

LITERATURE REVIEW: THE IMPLEMENTATION OF E-HEALTH AT PRIMARY HEALTHCARE CENTERS IN SURABAYA CITY

Background: The increasing number of patient visits in primary healthcare centers in Surabaya causes long duration of queue in a registration counter. To solve this problem, Surabaya Government has created an online registration system in each health service provider. The e-health is expected to give a positive impact on reducing the queue traffic at the registration counter.Aim: This study identified whether the online registration system or e-health which has been implemented by primary healthcare centers in Surabaya City is successful or not.Method: This study was a literature review which collected articles from Google Scholar databases published from 2015 until 2019. Fourteen articles were collected, but only 6 articles were discussed because of their relevant topics.Results: The review shows that e-health can simplify the process of patient registration and reduce patients’ waiting time for health service delivery. The success indicators of e-health program include its well-established system, effective information system, and excellent service for community. Obstacles found in the e-health implementation involve lack of thorough socialization of e-health. In turn, the community prefers a manual registration to e-health.Conclusion: The e-health service in primary healthcare centers in Surabaya City gives a positive effect on giving a fast and easy process in the registration procedure. However, there are still obstacles in implementing e-health due to lack of socialization. Keywords : queue, e-health, queuing time, primary healthcare centers.

The Reliability of Foot and Ankle Bone and Joint Kinematics Measured With Biplanar Videoradiography and Manual Scientific Rotoscoping.

The intricate motion of the small bones of the feet are critical for its diverse function. Accurately measuring the 3-dimensional (3D) motion of these bones has attracted much attention over the years and until recently, was limited to invasive techniques or quantification of functional segments using multi-segment foot models. Biplanar videoradiography and model-based scientific rotoscoping offers an exciting alternative that allows us to focus on the intricate motion of individual bones in the foot. However, scientific rotoscoping, the process of rotating and translating a 3D bone model so that it aligns with the captured x-ray images, is either semi- or completely manual and it is unknown how much human error affects tracking results. Thus, the aim of this study was to quantify the inter- and intra-operator reliability of manually rotoscoping in vivo bone motion of the tibia, talus, and calcaneus during running. Three-dimensional CT bone volumes and high-speed biplanar videoradiography images of the foot were acquired on six participants. The six-degree-of-freedom motions of the tibia, talus, and calcaneus were determined using a manual markerless registration algorithm. Two operators performed the tracking, and additionally, the first operator re-tracked all bones, to test for intra-operator effects. Mean RMS errors were 1.86 mm and 1.90° for intra-operator comparisons and 2.30 mm and 2.60° for inter-operator comparisons across all bones and planes. The moderate to strong similarity values indicate that tracking bones and joint kinematics between sessions and operators is reliable for running. These errors are likely acceptable for defining gross joint angles. However, this magnitude of error may limit the capacity to perform advanced analyses of joint interactions, particularly those that require precise (sub-millimeter) estimates of bone position and orientation. Optimizing the view and image quality of the biplanar videoradiography system as well as the automated tracking algorithms for rotoscoping bones in the foot are required to reduce these errors and the time burden associated with the manual processing.

Electromagnetic Navigation in Craniofacial Surgery Based on Automatic Registration of Dental Splints.

Optical navigation method cannot be used in partial craniofacial surgery due to light blocking. At present, electromagnetic navigation method can be used instead. The occlusal splint obtained from the patient's dental mold is used in the traditional electromagnetic navigation registration. Then, marker points are selected manually for registration through imaging data during the operation, which leads to the deviation of selection. In this study, the self-developed registration software was used to perform automatic registration in the intraoperative registration. Experimental results showed that it has higher accuracy and faster speed, and is suitable for the actual operation process in clinical environment compared with the traditional manual registration.

HeadLocNet: Deep convolutional neural networks for accurate classification and multi-landmark localization of head CTs.

Cochlear implants (CIs) are used to treat subjects with hearing loss. In a CI surgery, an electrode array is inserted into the cochlea to stimulate auditory nerves. After surgery, CIs need to be programmed. Studies have shown that the cochlea-electrode spatial relationship derived from medical images can guide CI programming and lead to significant improvement in hearing outcomes. We have developed a series of algorithms to segment the inner ear anatomy and localize the electrodes. But, because clinical head CT images are acquired with different protocols, the field of view and orientation of the image volumes vary greatly. As a consequence, visual inspection and manual image registration to an atlas image are needed to document their content and to initialize intensity-based registration algorithms used in our processing pipeline. For large-scale evaluation and deployment of our methods these steps need to be automated. In this article we propose to achieve this with a deep convolutional neural network (CNN) that can be trained end-to-end to classify a head CT image in terms of its content and to localize landmarks. The detected landmarks can then be used to estimate a point-based registration with the atlas image in which the same landmark set's positions are known. We achieve 99.5% classification accuracy and an average localization error of 3.45 mm for 7 landmarks located around each inner ear. This is better than what was achieved with earlier methods we have proposed for the same tasks.

Formalized Computer-Aided Handwriting Psychology: Validation and Integration into Psychological Assessment.

In contrast to traditional researches that involve a manual, non-quantitative, and subjective way of performing handwriting analysis, in the current research, a special computer-aided method of revised handwriting analysis is used. It includes the detection of personality traits via manual quantitative registration of handwriting signs and their automated quantitative evaluation. This method is based on a mathematical–statistical model that integrates multiple international publications on the evaluation of handwriting signs. The first aim is the validation of the revised method against the 16 Personality Factor Questionnaire Revised (16PF-R), which is performed as a self-report personality test by test persons and was developed and researched empirically by Raymond B. Cattell et al. A second aim is the development of an integrated model for assessment including handwriting analysis: when both methods come to the same result on a certain scale, then the construct can be accepted with higher reliability; in contrast, when results are contradictory, they should be regarded as a limitation of each method and raise awareness in the researchers, as these contradictions are a precious source of additional information regarding the complexity, ambiguity, and context specificity of personality traits.

The use of video camera to create metric 3D model of engineering objects

The article presents the possibilities of using a video camera to create a 3D metric model of engineering objects using Agisoft and CloudCompare software. Traditional photogrammetry technique does not always match up with production urgency needed by the market. Complexity is seen when used in huge objects leading to rise of cost, time and tediousness of the work. The use of Video Camera technique here termed as videogrammetry technique is comparable to taking pictures, however, it allows to speed up the process of obtaining data, which in many cases is a key element in anyb any project or research. The analysis of the quality of 3D modelling of the three filmed objects was performed, which allowed the authors to refine the procedure for acquiring images for spatial analyses. The applied technique of “videogrammetry” is comparable to taking pictures, but allows the data acquisition process to speed up, which in many cases is a key element in field research. 3D objects videos from no-metric camera were processed by Agisoft Metashape. To be able to assess the accuracy of the videogrammetry data, a well-established Laser scanner technique’s data was used for comparison. The laser scanner data were pre-processed in Autodesk Recap. Manual registration was performed utilizing 14 points from the three scans. The two 3D models were exported to CloudCompare software for comparison and further analysis. An analysis of the quality of 3D modelling of the three objects filmed was performed, which allowed refining the procedure for obtaining images for spatial analysis. The article presents the possibilities of using a non-metric mobile phone video camera “videogrammetry” to create a metric 3D model of engineering objects using Agisoft and CloudCompare software. In CloudCompare a registration, cloud to cloud (C2C) and profile to profile analysis was performed to determine the uncertainty of the 3D model produced from videogrammetry data determined as distance of separation between the two models. Results show average distance of separation between laser scanner and videogrammetry derived 3D model point cloud to be 34cm, the average profile separation was 25 cm in XY plane and 1.9 cm in Z-plane. Using Cloud to Cloud PCV the average difference of 84 cm was determined.

Building 3D Realistic Modeling Based on Air-ground Multi-source Data Fusion

Three-dimensional point cloud data is a new form of three-dimensional collection, which not only contains the geometric topology information of the object, but also has high simplicity and flexibility. In this paper, the air-ground multi-source data fusion technology is used to study the fine reconstruction of the 3D scene: based on the 3D laser scanning laser point cloud, the 3D spatial information of the ground visible objects is obtained, and the orthophoto obtained by the drone aerial photography is assisted, Obtain the three-dimensional space information of the top of the ground feature, and the ground three-dimensional laser scanner can quickly obtain the three-dimensional surface information of the building facade, ground, and trees. Due to the complex structure of the building and the occlusion of spatial objects, sub-station scanning is required when acquiring point cloud data. This article uses the Sino-German Energy Conservation Center Building of Shenyang Jianzhu University as the research area, using drone tilt photography technology and ground lidar technology to integrate. During the experiment, the field industry adopted the UAV image acquisition strategy of “automatic shooting of regular routes, supplemented by manual shooting of areas of interest”; in the field industry, the method of “manual coarse registration and ICP algorithm fine registration” The example results show that the ground 3D laser point cloud air-ground image fusion 3D modeling effect proposed in this paper is better and the quality is greatly improved, which makes up for the ground 3D laser scanning. In point cloud modeling, a large number of holes are insufficient due to occlusion and missing top information.

Intensity-based registration of bright-field and second-harmonic generation images of histopathology tissue sections.

The use of second-harmonic generation (SHG) microscopy in biomedical research is rapidly increasing. This is due in large part to the wide spread interest of using this imaging technique to examine the role of fibrillar collagen organization in diseases such as cancer. The co-examination of SHG images and traditional bright-field (BF) images of hematoxylin and eosin (H&E) stained tissue as a gold standard clinical validation is usually required. However, image registration of these two modalities has been mostly done by manually selecting corresponding landmarks which is labor intensive and error prone. We designed, implemented, and validated the first image intensity-based registration method capable of automatically aligning SHG images and BF images. In our algorithmic approach, a feature extractor is used to pre-process the BF image to block the content features not visible in SHG images and the output image is then aligned with the SHG image by maximizing the common image features. An alignment matrix maximizing the image mutual information is found by evolutionary optimization and the optimization is facilitated using a hierarchical multiresolution framework. The automatic registration results were compared to traditional manual registration to assess the performance of the algorithm. The proposed algorithm has been successfully used in several biomedical studies such as pancreatic and kidney cancer studies and shown great efficacy.

Retrospective Cohort Study on Vessel Deformation During Fenestrated or Branched Endovascular Aortic Repair; Traditional CTA Roadmaps Provide Insufficient and Inadequate Guidance During Target Vessel Cannulation

Introduction: Optimal visualization of target vessels in three-dimensions (3D) plays a key role in complex endovascular procedures, such as fenestrated and branched endovascular aortic repair (EVAR). A popular imaging technique to enhance target vessel visualization is image fusion. Image fusion combines real-time fluoroscopy with static preprocedural anatomical images, typically computed tomography angiography (CTA) to create an arterial roadmap. However, the introduction of stiff endovascular devices cause the arteries to stretch, leading to a mismatch between the actual position of the (origin of the) artery and its representation on the image fusion roadmap. This retrospective study assesses vessel deformation of the aorta and its side branches due to the introduction of a stiff endovascular devices, during fenestrated and branched EVAR. Furthermore, the influence of vascular tortuosity on the extent of vessel deformation was analysed. Methods: Patients that underwent fenestrated or branched EVAR between January 2015 and January 2018 were retrospectively included in this study. Two imaging datasets were collected from each patient: 1) the preoperative CTA and 2) the intraoperative contrast-enhanced cone beam computed tomography (ce-CBCT), acquired after the insertion of the stiff guidewire and stent delivery device (Zenith® custom made, Cook, Bloomington IN, USA) . Manual registration of both datasets was performed, using the bony landmarks of the vertebrae. Subsequently, the ostium of the celiac artery (CA), superior mesenteric artery (SMA), left renal artery (LRA) and right renal artery (RRA) were marked in both the CTA and ce-CBCT reconstructions. The ostium displacement of the four target vessels was reported as a 3D vector as well as a 2D vector in the coronal plane (RRA and LRA) or sagittal plane (CA and SMA). The tortuosity index of the iliac and the abdominal aortic segment were calculated. The effect of the tortuosity index on the extent of vessel deformation was assessed using linear regression. Results: In total 77 target vessels from 20 patients were included in this study. The 3D mean displacement vector of the ostium of the CA, SMA, RRA and LRA were respectively 8.7±3.8mm, 7.4±2.7mm, 7.9±2.7mm and 7.6±4.4mm. The 2D mean displacement vector for the SMA and CA in the sagittal viewing plane was 4.9±2.9mm and 6.5±3.0mm respectively. The 2D mean displacement vector of the RRA and LRA in the coronal viewing plane was 7.0±2.8mm 6.2±4.3mm respectively. An example of the 2D displacement of the RRA in the coronal plane is shown in Figure 1. In total, 74% of the target vessels had a 2D vector displacement of more than 50% of the diameter of the vessel. The mean tortuosity index of the abdominal aortic segment and the iliac segment was 1.10 and 1.34 respectively. Linear regression showed no association between the extend of vessel displacement and the tortuosity index of the abdominal aortic segment (p=0.37), nor the iliac segment (p=0.11). Conclusion: There is significant vessel displacement of the ostium of the target vessels, during fenestrated and branched EVARs caused by the introduction of stiff endovascular devices. Consequently, preoperative CTA roadmaps are inadequate to guide target vessel cannulation during fenestrated or branched EVAR. Disclosure: Nothing to disclose

PENGUATAN KAPASITAS BUMG BERSAMA MINAPOLITAN MEURASA SABAN KABUPATEN ACEH TIMUR MELALUI EDUTEKNOPRENEURSHIP

Gampong-Owned Enterprises (BUMG) Minapolitan Meurasa Saban is a business entity owned by 5 villages (bale buya, matang gleum, kuala leuge, seuneubok peusangan and seuneubok pidie). with one of their business is BUMDES Mart Minapolitan Meurasa Saban. The weakness of administrative and financial as well as manual product registration are problems encountered in marketing the products on display at BUMG. The purpose of this program is to improve administrative and financial management staffs based on edutechnopreneurship. The activity was carried out for 5 months starting from May to September 2019. The activities involved 15 BUMG management and supervisors of Minapolitan Meurasa Saban. The method used is discussion and active participation of the target group by applying adult learning model. The activities were carried out in several stages which included coordination, socialization, training and mentoring activities. The results of the evaluation of the implementation of the activity showed that there was an increase in the capacity of BUMG's Bersama Minapolitan Meurasa Saban supervisors and management staffs on improving BUMG's administrative and financial governance. The results of the questionnaire showed that 10 administrators (75%) understood all the training material well, while 5 administrators (25%) understood all the training material. The level of satisfaction of the training participants showed 12 managers (85%) were very satisfied and 3 administrators (15%) were satisfied with the implementation of the training. BUMG Bersama Minapolitan Meurasa Saban supervisors and administrators have understood AD / ART and TUPOKSI, whereas the treasurer and operator of BUMG Bersama Minapolitan Meurasa Saban are able to understand the edutechnopreneurship-based product registration, BUMG Bersama Minapolitan Meurasa Saban has a business development plan as stated in the annual work programKey word: BUMG Bersama Minapolitan Meurasa Saban, Aceh Timur District, Edutechnopreneurship

Fully automated convolutional neural network-based affine algorithm improves liver registration and lesion co-localization on hepatobiliary phase T1-weighted MR images

BackgroundLiver alignment between series/exams is challenged by dynamic morphology or variability in patient positioning or motion. Image registration can improve image interpretation and lesion co-localization. We assessed the performance of a convolutional neural network algorithm to register cross-sectional liver imaging series and compared its performance to manual image registration.MethodsThree hundred fourteen patients, including internal and external datasets, who underwent gadoxetate disodium-enhanced magnetic resonance imaging for clinical care from 2011 to 2018, were retrospectively selected. Automated registration was applied to all 2,663 within-patient series pairs derived from these datasets. Additionally, 100 within-patient series pairs from the internal dataset were independently manually registered by expert readers. Liver overlap, image correlation, and intra-observation distances for manual versus automated registrations were compared using paired t tests. Influence of patient demographics, imaging characteristics, and liver uptake function was evaluated using univariate and multivariate mixed models.ResultsCompared to the manual, automated registration produced significantly lower intra-observation distance (p < 0.001) and higher liver overlap and image correlation (p < 0.001). Intra-exam automated registration achieved 0.88 mean liver overlap and 0.44 mean image correlation for the internal dataset and 0.91 and 0.41, respectively, for the external dataset. For inter-exam registration, mean overlap was 0.81 and image correlation 0.41. Older age, female sex, greater inter-series time interval, differing uptake, and greater voxel size differences independently reduced automated registration performance (p ≤ 0.020).ConclusionA fully automated algorithm accurately registered the liver within and between examinations, yielding better liver and focal observation co-localization compared to manual registration.

Application value of augmented reality technology in pancreatoduodenectomy

Objective To investigate the application value of augmented reality (AR) technology in pancreatoduodenectomy (PD). Methods The retrospective and descriptive study was conducted. The clinicopathological data of 3 male patients who underwent PD in Tsinghua University Affiliated Beijing Tsinghua Changgung Hospital from June 2018 to February 2019 were collected. The 3 patients were aged from 52 to 63 years, with a median age of 57 years. Digital imaging and communication standard format data of enhanced computed tomography (CT) scan were collected, the three-dimensional (3D) images of abdominal arteries, portal vein, descending duodenum, pancreatic body and tail, pancreatic head, common bile duct, and pancreatic duct were reconstructed. The results were imported into the AR software. Optical tracking based on two-dimensional codes and manual interactive rigid registration were adopted for intraoperative navigation. Observation indicators: (1) surgical and postoperative conditions; (2) postoperative pathological examination; (3) follow-up. Follow-up using outpatient examination or telephone interview was conducted to detect survival of patients and tumor metastasis and recurrence up to June 2019. The measurement data with skewed distribution were expressed as M (range). Count data were expressed as absolute numbers. Results (1) Surgical and postoperative conditions: all the 3 patients underwent PD with AR technology as intraoperative navigation successfully. The operation time, volume of intraoperative blood loss, and duration of postoperative hospital stay were 6 hours (range, 5-8 hours), 700 mL (range, 300-900 mL), 11 days (range, 9-12 days). There was no perioperative death or complication occured. After surgery, the patients who underwent PD combined with superior mesenteric vein (SMV) resection and reconstruction had patent SMV on the enhanced computed tomography examination. (2) Postoperative pathological examination: results of pathological examination showed 1 case of intraductal papillary mucinous neoplasm (IPMN) of the pancreas with invasive adenocarcinoma (neoplasm invading SMV), 1 case of insulinoma, and 1 case of periampullary neuroendocrine carcinoma, respectively. (3) Follow-up: 3 patients were followed up for 4-12 months, with a median follow-up time of 6 months. During the follow-up, the patient with IPMN of the pancreas and invasive adenocarcinoma had liver metastasis at 3 months after surgery, and received chemotherapy at other hospital. After 4 cycles of chemotherapy, the metastatic nodule shrank, and the patient was still in follow-up up to deadline of follow-up. Other 2 patients had no recurrence or metastasis. Conclusion AR technique assisted PD is safe and feasible, which is helpful to indentify vascular branches and tracks. Key words: Pancreatic neoplasms; Augmented reality technology; Three-dimensional reconstruction; Pancreatoduodenectomy; Surgical navigation

Identifying the Sources of Error When Using 3-Dimensional Printed Head Models with Surgical Navigation

The evaluation of sources of error when preparing, printing, and using 3-dimensional (3D) printed head models for training purposes. Two 3D printed models were designed and fabricated using actual patient imaging data with reference marker points embedded artificially within these models that were then registered to a surgical navigation system using 3 different methods. The first method uses a conventional manual registration, using the actual patient's imaging data. The second method is done by directly scanning the created model using intraoperative computed tomography followed by registering the model to a new imaging dataset manually. The third is similar to the second method of scanning the model but eventually uses an automatic registration technique. The errors for each experiment were then calculated based on the distance of the surgical navigation probe from the respective positions of the embedded marker points. Errors were found in the preparation and printing techniques, largely depending on the orientation of the printed segment and postprocessing, but these were relatively small. Larger errors were noted based on a couple of variables: if the models were registered using the original patient imaging data as opposed to using the imaging data from directly scanning the model (1.28 mm vs. 1.082 mm), and the accuracy was best using the automated registration techniques (0.74 mm). Spatial accuracy errors occur consistently in every 3D fabricated model. These errors are derived from the fabrication process, the image registration process, and the surgical process of registration.

A Marker-Less Registration Approach for Mixed Reality-Aided Maxillofacial Surgery: a Pilot Evaluation.

As of common routine in tumor resections, surgeons rely on local examinations of the removed tissues and on the swiftly made microscopy findings of the pathologist, which are based on intraoperatively taken tissue probes. This approach may imply an extended duration of the operation, increased effort for the medical staff, and longer occupancy of the operating room (OR). Mixed reality technologies, and particularly augmented reality, have already been applied in surgical scenarios with positive initial outcomes. Nonetheless, these methods have used manual or marker-based registration. In this work, we design an application for a marker-less registration of PET-CT information for a patient. The algorithm combines facial landmarks extracted from an RGB video stream, and the so-called Spatial-Mapping API provided by the HMD Microsoft HoloLens. The accuracy of the system is compared with a marker-based approach, and the opinions of field specialists have been collected during a demonstration. A survey based on the standard ISO-9241/110 has been designed for this purpose. The measurements show an average positioning error along the three axes of (x, y, z) = (3.3 ± 2.3, - 4.5 ± 2.9, - 9.3 ± 6.1) mm. Compared with the marker-based approach, this shows an increment of the positioning error of approx. 3mm along two dimensions (x, y), which might be due to the absence of explicit markers. The application has been positively evaluated by the specialists; they have shown interest in continued further work and contributed to the development process with constructive criticism.

A "eye-in-body" integrated surgery robot system for stereotactic surgery.

Current stereotactic surgical robots system relies on cumbersome operations such as calibration, tracking and registration to establish the accurate intraoperative coordinate transformation chain, which makes the system not easy to use. To overcome this problem, a novel stereotactic surgical robot system has been proposed and validated. First, a hand-eye integrated scheme is proposed to avoid the intraoperative calibration between robot arm and motion tracking system. Second, a special reference-tool-based patient registration and tracking method is developed to avoid intraoperative registration. Third, a model-free visual servo method is used to reduce the accuracy requirement of hand-eye relationship and robot kinematic model. Finally, a prototype of the system is constructed and performance tests and a pedicle screw drilling experiment are performed. The results show that the proposed system has acceptable accuracy. The target positioning error in the plane was - 0.68 ± 0.52mm and 0.06 ± 0.41mm. The orientation error was 0.43 ± 0.25°. The pedicle screw drilling experiment shows that the system can complete accurate stereotactic surgery. The stereotactic surgical robot system described in this paper can perform stereotactic surgery without the intraoperative hand-eye calibration and nor manual registration and can achieve an acceptable position and orientation accuracy while tolerating the errors in the hand-eye coordinate transformation error and the robot kinematics model error.

PRICE REGISTRATION AT EVENTS PT. PACTOCONVEX NIAGATAMA CASE STUDY DASABAKTI SMI 2019 &amp; GROUP MEETING EGMONT 2019

Registration Process of PT. Pactoconvex Niagatama Event Case Study of Dasabakti SMI 2019 &amp; Egmont Group Meetings 2019 . This Final Project task discusses a case study of the participants registration from two events managed by PT. Pactoconvex Niagatama, There are Dasabakti PT. SMI 2019 event that used the manual registration system, and the Egmont Group Meetings 2019 Event that used online registration system. The results of this case study are that the online registration system has better and safer in handling participants data and more efficient than the manual registration system. In addition, the author also wrote about the function of registration in an event and which registration methods are commonly used at an event. Keywords : Registration, Event, MICE, Method/Mode

Comparison of different registration methods and landmarks for image-guided radiation therapy of pulmonary tumors

BackgroundTo compare the accuracy, advantages and disadvantages of automatic registration methods at different anatomical-sites for thoracic image-guided radiation therapy (IGRT).MethodsThe Varian-IX IGRT system was used to perform a manual registration of the images collected on the first fraction of 60 patients with lung cancer (42 cases central location and 18 cases of peripheral). The registered images were used as reference images. Offline registration was performed for computed tomography-CBCT images using four methods: whole image registration, ipsilateral registration, soft tissue tumor registration, and vertebral body registration. Time taken to complete and deviation value were analyzed between the different methods.ResultsThere were significant differences in absolute deviation value of all the three directions (P < 0.001) and the time consumption (P < 0.001) between 4 methods. The Z direction had significant differences in deviation value of 4 methods (0.023 ± 0.128 mm, − 0.030 ± 0.175 mm, − 0.010 ± 0.238 mm, − 0.075 ± 0.137 mm, P = 0.011). The difference was significant in the X direction of the ipsilateral registration method between central and peripheral lung cancer (0.033 ± 0.053 mm vs. 0.067 ± 0.067 mm, P = 0.045).ConclusionsThe whole lung or affected side registration methods could be recommended to be used in the automatic registration function of the Varian-IX’s On-Board Imaging (OBI) system.