Amir M. Tahmasebi

Dynamic parameter identification and analysis of a PHANToM haptic device

In this paper, the dynamics of a SensAble Technologies PHANToM Premium 1.5 haptic device is experimentally identified and analyzed. Towards this purpose, the dynamic model derived in the work of M. C. Cavusoglu and D. Feygin (2001) is augmented with a friction model and is linearly parameterized. The identified model predicts joint torques with over 95% accuracy and produces an inertia matrix that is confirmed to be positive-definite within the device workspace. In addition, user hand force estimates with and without including the identified dynamics are compared with the measured values. The experiments are also conducted for other typical installation conditions of the device, such as with force sensor mounted at the end-effector, using gimbal and counterbalance weight, and upside-down installation of the device. The identified dynamic model can be used for hand force estimation, accurate gravity counterbalancing for different installation conditions, and model-based control systems design for haptic simulation and tele-operation applications

Reducing inter-subject anatomical variation: Effect of normalization method on sensitivity of functional magnetic resonance imaging data analysis in auditory cortex and the superior temporal region

Conventional group analysis of functional MRI (fMRI) data usually involves spatial alignment of anatomy across participants by registering every brain image to an anatomical reference image. Due to the high degree of inter-subject anatomical variability, a low-resolution average anatomical model is typically used as the target template, and/or smoothing kernels are applied to the fMRI data to increase the overlap among subjects image data. However, such smoothing can make it difficult to resolve small regions such as subregions of auditory cortex when anatomical morphology varies among subjects. Here, we use data from an auditory fMRI study to show that using a high-dimensional registration technique (HAMMER) results in an enhanced functional signal-to-noise ratio (fSNR) for functional data analysis within auditory regions, with more localized activation patterns. The technique is validated against DARTEL, a high-dimensional diffeomorphic registration, as well as against commonly used low-dimensional normalization techniques such as the techniques provided with SPM2 (cosine basis functions) and SPM5 (unified segmentation) software packages. We also systematically examine how spatial resolution of the template image and spatial smoothing of the functional data affect the results. Only the high-dimensional technique (HAMMER) appears to be able to capitalize on the excellent anatomical resolution of a single-subject reference template, and, as expected, smoothing increased fSNR, but at the cost of spatial resolution. In general, results demonstrate significant improvement in fSNR using HAMMER compared to analysis after normalization using DARTEL, or conventional normalization such as cosine basis function and unified segmentation in SPM, with more precisely localized activation foci, at least for activation in the region of auditory cortex.

Is the Link between Anatomical Structure and Function Equally Strong at All Cognitive Levels of Processing

Whereas low-level sensory processes can be linked to macroanatomy with great confidence, the degree to which high-level cognitive processes map onto anatomy is less clear. If function respects anatomy, more accurate intersubject anatomical registration should result in better functional alignment. Here, we use auditory functional magnetic resonance imaging and compare the effectiveness of affine and nonlinear registration methods for aligning anatomy and functional activation across subjects. Anatomical alignment was measured using normalized cross-correlation within functionally defined regions of interest. Functional overlap was assessed using t-statistics from the group analyses and the degree to which group statistics predict high and consistent signal change in individual data sets. In regions related to early stages of auditory processing, nonlinear registration resulted in more accurate anatomical registration and stronger functional overlap among subjects compared with affine. In frontal and temporal areas reflecting high-level processing of linguistic meaning, nonlinear registration also improved the accuracy of anatomical registration. However, functional overlap across subjects was not enhanced in these regions. Therefore, functional organization, relative to anatomy, is more variable in the frontal and temporal areas supporting meaning-based processes than in areas devoted to sensory/perceptual auditory processing. This demonstrates for the first time that functional variability increases systematically between regions supporting lower and higher cognitive processes.

A novel adaptive approach to fingerprint enhancement filter design

A novel procedure for fingerprint enhancement filter design is described. Fingerprints are best used as unique and invariant identifiers of individuals. Identification of fingerprint images is based on matching the features obtained from a query image against those stored in a database. Poor quality of fingerprint images makes serious problems in the performance of subsequent matching process. The main contribution of this work is to quantify and justify the functional relationship between image features and filter parameters. In this work, the enhancement process is adapted to the input image characteristics to improve its efficiency. Experimental results show the superiority of the proposed enhancement algorithm compared to the best fingerprint enhancement procedures reported in the literature.

A Framework for the Design of a Novel Haptic-Based Medical Training Simulator

This paper presents a framework for the design of a haptic-based medical ultrasound training simulator. The proposed simulator is composed of a PHANToM haptic device and a modular software package that allows for visual feedback and kinesthetic interactions between an operator and multimodality image databases. The system provides real-time ultrasound images in the same fashion as a typical ultrasound machine, enhanced with corresponding augmented computerized tomographic (CT) and/or MRI images. The proposed training system allows trainees to develop radiology techniques and knowledge of the patients anatomy with minimum practice on live patients, or in places or at times when radiology devices or patients with rare cases may not be available. Low-level details of the software structure that can be migrated to other similar medical simulators are described. A preliminary human factors study, conducted on the prototype of the developed simulator, demonstrates the potential usage of the system for clinical training.

Experimental identification and analysis of the dynamics of a phantom premium 1.5a haptic device

The dynamics of a PHANToM Premium 1.5A haptic device from SensAble Technologies, Inc. is experimentally identified and analyzed for different installations of the device and its accessories, such as the typical upright, upside down, with gimbal and counterbalance weight, and with force sensor.1 An earlier formulation of the robot dynamic model is augmented with a friction model, linearly parameterized, and experimentally identified using least squares. The identified dynamics are experimentally evaluated with an inverse dynamics controller and verified by comparing user hand force estimates with the measured values. The contribution of different dynamic terms such as inertial, Coriolis and centrifugal, gravitational, and Coulomb and viscous friction are demonstrated and discussed. The identified model can be used for a variety of haptic applications, such as hand force estimation, accurate active gravity compensation and counterbalance weight determination for various installation conditions, and model-based control for haptic simulation and teleoperation.

A haptic-based system for medical image examination

This work presents a haptic-based simulator for training of radiology residents and sonographers. The system consists of a force feedback haptic device providing means to interact in real-time with volumetric images of a virtual patient, captured pre-operatively from several subjects. The training system allows trainees to develop radiology techniques and knowledge of the patients anatomy with minimum practice on live patients, or in places or at times when radiology devices or patients with rare cases may not be available. The haptic interface guarantees position correspondence between the operators hand and a virtual probe position that slices medical volume sets in the plane of the probe. Thus the simulated procedure becomes nearly identical to the real examinations at the hospital. Different configurations of the system are implemented and presented. Future potential applications for the system are discussed as well.

A validation framework for probabilistic maps using Heschl's gyrus as a model.

Probabilistic maps are useful in functional neuroimaging research for anatomical labeling and for data analysis. The degree to which a probability map can accurately estimate the location of a structure of interest in a new individual depends on many factors, including variability in the morphology of the structure of interest over subjects, the registration (normalization procedure and template) applied to align the brains among individuals for constructing a probability map, and the registration used to map a new subjects data set to the frame of the probabilistic map. Here, we take Heschls gyrus (HG) as our structure of interest, and explore the impact of different registration methods on the accuracy with which a probabilistic map of HG can approximate HG in a new individual. We assess and compare the goodness of fit of probability maps generated using five different registration techniques, as well as evaluating the goodness of fit of a previously published probabilistic map of HG generated using affine registration (Penhune et al., 1996). The five registration techniques are: three groupwise registration techniques (implicit reference-based or IRG, DARTEL, and BSpline-based); a high-dimensional pairwise registration (HAMMER) as well as a segmentation-based registration (unified segmentation of SPM5). The accuracy of the resulting maps in labeling HG was assessed using evidence-based diagnostic measures within a leave-one-out cross-validation framework. Our results demonstrated the out performance of IRG and DARTEL compared to other registration techniques in terms of sensitivity, specificity and positive predictive value (PPV). All the techniques displayed relatively low sensitivity rates, despite high PPV, indicating that the generated probability maps provide accurate but conservative estimates of the location and extent of HG in new individuals.

A New Approach for Creating Customizable Cytoarchitectonic Probabilistic Maps without a Template

We present a novel technique for creating template-free probabilistic maps of the cytoarchitectonic areas using a groupwise registration. We use the technique to transform 10 human post-mortem structural MR data sets, together with their corresponding cytoarchitectonic information, to a common space. We have targeted the cytoarchitectonically defined subregions of the primary auditory cortex. Thanks to the template-free groupwise registration, the created maps are not macroanatomically biased towards a specific geometry/topology. The advantage of the group-wise versus pairwise registration in avoiding such anatomical bias is better revealed in studies with small number of subjects and a high degree of variability among the individuals such as the post-mortem data. A leave-one-out cross-validation method was used to compare the sensitivity, specificity and positive predictive value of the proposed and published maps. We observe a significant improvement in localization of cytoarchitectonically defined subregions in primary auditory cortex using the proposed maps. The proposed maps can be tailored to any subject space by registering the subject image to the average of the groupwise-registered post-mortem images.

Software structure design for a haptic-based medical examination system

This paper presents a novel approach to software structure design of a haptic-based medical examination simulator. The proposed software is implemented in a fully object-oriented structure that provides real-time interaction with a PHANToM/spl trade/ haptic device, as a diagnostic tool for medical experts. The software allows radiology experts to visualize, display and interact with the graphical model of a patients pre-scanned organ or tissue. The expert is also able to re-slice through pre-registered model data sets and view the 2D reslice images in different modalities simultaneously. The haptic interface guarantees position correspondence between the operators hand and a virtual probe. Thus the simulated procedure emulates actual examinations condition in clinic. Our preliminary human factors study at Kingston General Hospital with radiology residents have demonstrated the significant potential of the developed software for scientific and commercial applications.