Xiaopeng Yang

A hybrid semi-automatic method for liver segmentation based on level-set methods using multiple seed points

The present study developed a hybrid semi-automatic method to extract the liver from abdominal computerized tomography (CT) images. The proposed hybrid method consists of a customized fast-marching level-set method for detection of an optimal initial liver region from multiple seed points selected by the user and a threshold-based level-set method for extraction of the actual liver region based on the initial liver region. The performance of the hybrid method was compared with those of the 2D region growing method implemented in OsiriX using abdominal CT datasets of 15 patients. The hybrid method showed a significantly higher accuracy in liver extraction (similarity index, SI=97.6 ± 0.5%; false positive error, FPE = 2.2 ± 0.7%; false negative error, FNE=2.5 ± 0.8%; average symmetric surface distance, ASD=1.4 ± 0.5mm) than the 2D (SI=94.0 ± 1.9%; FPE = 5.3 ± 1.1%; FNE=6.5 ± 3.7%; ASD=6.7 ± 3.8mm) region growing method. The total liver extraction time per CT dataset of the hybrid method (77 ± 10 s) is significantly less than the 2D region growing method (575 ± 136 s). The interaction time per CT dataset between the user and a computer of the hybrid method (28 ± 4 s) is significantly shorter than the 2D region growing method (484 ± 126 s). The proposed hybrid method was found preferred for liver segmentation in preoperative virtual liver surgery planning.

Development of A User-Centered Virtual Liver Surgery Planning System

The present study is intended to develop a user-centered virtual liver surgery planning system called Dr. Liver which has clinical applicability and effectiveness to support liver surgery. Existing virtual surgery systems needs to be customized to liver surgery and improved for better usability and time efficiency. A use scenario of a virtual liver surgery planning system was established through literature review, benchmarking, and interviews with surgeons. Based on the use scenario, detailed liver surgery planning procedures were defined. The major functions of Dr. Liver include (1) extraction of the liver, vessels, and tumors from abdominal CT images, (2) estimation of the standard liver volume of a patient, (3) volumetry of the extracted liver, vessels, and tumors, (4) segmentation of the liver into 8 segments based on structures of the extracted portal and hepatic veins, and (5) support of surgery planning. Novel algorithms were developed and implemented into Dr. Liver for accuracy and time efficiency. Various user-friendly features such as a procedural interface of virtual liver surgery planning were integrated into Dr. Liver for better usability. Dr. Liver would be applied to safe and rational planning of liver surgery.

Development of an Analysis System for Biosignal and Driving Performance Measurements

An analysis of biosignal and performance data collected during driving has increasingly employed in research to explore a human-vehicle interface design for better safety and comfort. The present study developed a protocol and a system to effectively analyze biosignal and driving performance measurements in various driving conditions. Electrocardiogram (ECG), respiration rate (RR), and skin conductance level (SCL) were selected for biosignal analysis in the study. A data processing and analysis protocol was established based on a comprehensive review of related literature. Then, the established analysis protocol was implemented to a computerized system so that immense data of biosignal and driving performance can be analyzed with ease, efficiency, and effectiveness for an individual and/or a group of individuals of interest. The developed analysis system would be of use to examine the effects of driving conditions to cognitive workload and driving performance. Keyword: Biosignal, Driving performance, Analysis protocol, Computerized analysis system

Application of massive 3D head and facial scan datasets in ergonomic head-product design

3D human body scan datasets have been collected and various techniques of post-processing, size and shape analysis, and applications in product design have been introduced. This paper is aimed to introduce techniques and cases of head-product design studies based on massive 3D head scan datasets. 3D scan datasets of the head, face and ear were collected and post-processed by editing, landmarking, alignment and measurement. For useful application of the 3D head scan datasets in head-product designs, we applied several analysis techniques such as development of a sizing system, selection of representative models, analysis of shape variation based on template-registered 3D scans and analysis of virtual fit. This paper can help understand an overview of techniques regarding massive 3D scan datasets and their applications to ergonomic product design.

Dr. Liver: A preoperative planning system of liver graft volumetry for living donor liver transplantation

BACKGROUND AND OBJECTIVE Manual tracing of the right and left liver lobes from computed tomography (CT) images for graft volumetry in preoperative surgery planning of living donor liver transplantation (LDLT) is common at most medical centers. This study aims to develop an automatic system with advanced image processing algorithms and user-friendly interfaces for liver graft volumetry and evaluate its accuracy and efficiency in comparison with a manual tracing method. METHODS The proposed system provides a sequential procedure consisting of (1) liver segmentation, (2) blood vessel segmentation, and (3) virtual liver resection for liver graft volumetry. Automatic segmentation algorithms using histogram analysis, hybrid level-set methods, and a customized region growing method were developed. User-friendly interfaces such as sequential and hierarchical user menus, context-sensitive on-screen hotkey menus, and real-time sound and visual feedback were implemented. Blood vessels were excluded from the liver for accurate liver graft volumetry. A large sphere-based interactive method was developed for dividing the liver into left and right lobes with a customized cutting plane. The proposed system was evaluated using 50 CT datasets in terms of graft weight estimation accuracy and task completion time through comparison to the manual tracing method. The accuracy of liver graft weight estimation was assessed by absolute difference (AD) and percentage of AD (%AD) between preoperatively estimated graft weight and intraoperatively measured graft weight. Intra- and inter-observer agreements of liver graft weight estimation were assessed by intraclass correlation coefficients (ICCs) using ten cases randomly selected. RESULTS The proposed system showed significantly higher accuracy and efficiency in liver graft weight estimation (AD = 21.0 ± 18.4 g; %AD = 3.1% ± 2.8%; percentage of %AD > 10% = none; task completion time = 7.3 ± 1.4 min) than the manual tracing method (AD = 70.5 ± 52.1 g; %AD = 10.2% ± 7.5%; percentage of %AD > 10% = 46%; task completion time = 37.9 ± 7.0 min). The proposed system showed slightly higher intra- and inter-observer agreements (ICC = 0.996 to 0.998) than the manual tracing method (ICC = 0.979 to 0.999). CONCLUSIONS The proposed system was proved accurate and efficient in liver graft volumetry for preoperative planning of LDLT.

Estimation of Standard Liver Volume Using CT Volume, Body Composition, and Abdominal Geometry Measurements

Purpose The present study developed formulas for estimation of standard liver volume (SLV) with high accuracy for the Korean population. Materials and Methods SLV estimation formulas were established using gender-balanced and gender-unbalanced measurements of anthropometric variables, body composition variables, and abdominal geometry of healthy Koreans (n=790). Total liver volume excluding blood volume, was measured based on CT volumetry. Results SLV estimation formulas as preferred in various conditions of data availability were suggested in the present study. The suggested SLV estimation formulas in the present study were found superior to existing formulas, with an increased accuracy of 4.0–217.5 mL for absolute error and 0.2–18.7% for percentage of absolute error. Conclusion SLV estimation formulas using gender-balanced measurements showed better performance than those using gender-unbalanced measurements. Inclusion of body composition and abdominal geometry variables contributed to improved performance of SLV estimation.

Estimation of Instantaneous Hand Joint Centers of Rotation Using 3D Reconstructed Hand Skeleton Motion from CT Scans

The present study estimated instantaneous hand joint centers of rotation (CoR) using 3D reconstructed hand skeleton motions captured from CT scan. We proposed a novel method for estimation of instantaneous joint CoR using the same bone surfaces for different hand postures. Each bone in a template hand posture was registered to the corresponding bone of different hand postures. The registered hand postures (having the same bone surfaces as the template hand posture but different postures) with the template hand posture were then used for estimation of instantaneous joint CoR. The proposed method performed better than the existing methods in estimation of instantaneous joint CoR. Consistency of instantaneous joint CoRs determined in the same rotation angle range was improved by 31.7% to 51.0% in the proposed method. The present study focused on distal interphalangeal (DIP) and proximal interphalangeal (PIP) joints of the index finger of a participant. Joints of the whole hands of more participants will be studied for further generalization of the findings.

Anthropometric analysis of 3D ear scans of Koreans and Caucasians for ear product design

Abstract The present study measured 25 dimensions of the ear including the concha and ear canal for ergonomic design of ear products and compared with existing ear measurement studies. Scanning and casting methods were employed to produce 3D ear images for 230 Koreans and 96 Caucasians and measurements of the ear dimensions were obtained by identifying 21 landmarks on individual ear scan image. The Korean ear measurements were found significantly larger (mean difference  = 0.4–3.7 mm) and more varied (ratio of SDs =1.01–1.55) than those of Caucasians in most of ear dimensions. The average ear length and ear breadth of male were significantly longer ( = 1.3–7.0 mm) and wider ( = 0.8–3.0 mm) than those of female. Use of gender- and ethnicity-composite ear data is recommended in product design due to the much larger intra-population variations (7.5–22.2 mm) than the corresponding inter-population variations. Practitioner Summary: The 3D ear measurements of Koreans and Caucasians were collected and compared with those of different ethnic populations. The distinct ear features of the populations identified in this study are applicable to ergonomic design of ear products with better fit and comfort. Abbreviations: CCW: cavum concha width; CV: coefficient of variation; EB: ear breadth; EL: ear length; SD: standard deviation; SE: sampling error; 3D: 3 dimensional

An Ergonomic Grip Design Process for Vaginal Ultra Sound Probe Based on Analyses of Benchmarking, Hand Data, and Grip Posture

The present study presents a systematic design process for the ergonomic design of a vaginal probe based on benchmarking, hand data, and grip posture analyses. Five existing vaginal grip designs were compared with each other using subjective measures to identify preferred design features for a new probe grip design. An in-depth analysis of the relationships between grip design variables and hand dimensions was conducted along with the consideration of preferred grip postures of vaginal probe and hand measurements. Two novel vaginal probe grip designs were proposed based on the analysis results of benchmarking, hand data, and grip posture. A validation experiment showed a significant improvement of the hand-data based vaginal grip design compared with the existing designs in terms of subjective satisfaction and wrist flexion.

A 3D anthropometric sizing analysis system based on North American CAESAR 3D scan data for design of head wearable products

Abstract The present study developed a sizing analysis system for head-related product designs based on the Civilian American and European Surface Anthropometry Resource (CAESAR) database of North Americans. A total of 2299 heads in the CAESAR database were manually edited and 26 anthropometric landmarks were marked on the edited 3D heads to measure 30 anthropometric dimensions related to head-related product designs. The 3D anthropometric sizing analysis system (3D-ASAS) developed in the study provides analysis functions of a sizing system and representative face models by considering a target product, a target population, the number of size categories, and key anthropometric dimensions based on the CAESAR head measurements. Further research to reduce the efforts of manual editing and landmarking of 3D body scan data is discussed for efficient application of the 3D-ASAS to the design process of various wearable products.