Ultra-High Field Strength MR Image-Guided Robotic Needle Delivery Device for In-Bore Small Animal Interventions

Current methods of accurate soft tissue injections in small animals are prone to many sources of error. Although efforts have been made to improve the accuracy of needle deliveries, none of the efforts have provided accurate soft tissue references. An MR image-guided robot was designed to function inside the bore of a 9.4T MR scanner to accurately deliver needles to locations within the mouse brain. The robot was designed to have no noticeable negative effects on the image quality and was localized in the MR images through the use of an MR image visible fiducial. The robot was mechanically calibrated and subsequently validated in an image-guided phantom experiment, where the mean needle targeting accuracy and needle trajectory accuracy were calculated to be 178 ± 54µm and 0.27 ± 0.65º, respectively. Finally, the device successfully demonstrated an image-guided needle targeting procedure in situ

Technique and application of a non-invasive three dimensional image matching method for the study of total shoulder arthroplasty

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2009.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.MIT Institute Archives copy: with CD-ROM; divisional library copy with no CD-ROM.Includes bibliographical references (p. 99-104).Knowledge of in-vivo glenohumeral joint biomechanics after total shoulder arthroplasty are important for the improvement of patient function, implant longevity and surgical technique. No data has been published on the in-vivo glenohumeral joint contact locations in patients after total shoulder arthroplasty. Therefore, the objectives of this thesis were to determine the in-vivo glenohumeral joint contact locations and humeral head translations in patients after total shoulder arthroplasty. First, a non-invasive three dimensional fluoroscopic image matching method was developed and validated for use in the shoulder joint complex. Next, a group of patients that have undergone clinically successful total shoulder arthroplasty surgeries were recruited for study and imaged by the fluoroscopic imaging technique.The fluoroscopic imaging system was recreated in a virtual environment and the in vivo kinematics that were recorded by the fluoroscopes were recreated with three dimensional models. The contact centroids of the glenohumeral joint and humeral head translations were measured using solid modeling software. In summary, this thesis quantified the in-vivo glenohumeral joint contact locations and humeral head translations after total shoulder arthroplasty. These data provides surgeons and engineers valuable information for developing surgical treatments that may better help recreate 'normal' motion of the shoulder after total shoulder arthroplasty.by Daniel Frank Massimini.S.M

Towards a Conceptual Design of an Intelligent Material Transport Based on Machine Learning and Axiomatic Design Theory

Reliable and efficient material transport is one of the basic requirements that affect productivity in sheet metal industry. This paper presents a methodology for conceptual design of intelligent material transport using mobile robot, based on axiomatic design theory, graph theory and artificial intelligence. Developed control algorithm was implemented and tested on the mobile robot system Khepera II within the laboratory model of manufacturing environment. Matlab© software package was used for manufacturing process simulation, implementation of search algorithms and neural network training. Experimental results clearly show that intelligent mobile robot can learn and predict optimal material transport flows thanks to the use of artificial neural networks. Achieved positioning error of mobile robot indicates that conceptual design approach can be used for material transport and handling tasks in intelligent manufacturing systems