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Full-Text Articles in Engineering
Atlas-Based Shared-Boundary Deformable Multi-Surface Models Through Multi-Material And Two-Manifold Dual Contouring, Tanweer Rashid, Sharmin Sultana, Mallar Chakravarty, Michel Albert Audette
Atlas-Based Shared-Boundary Deformable Multi-Surface Models Through Multi-Material And Two-Manifold Dual Contouring, Tanweer Rashid, Sharmin Sultana, Mallar Chakravarty, Michel Albert Audette
Electrical & Computer Engineering Faculty Publications
This paper presents a multi-material dual “contouring” method used to convert a digital 3D voxel-based atlas of basal ganglia to a deformable discrete multi-surface model that supports surgical navigation for an intraoperative MRI-compatible surgical robot, featuring fast intraoperative deformation computation. It is vital that the final surface model maintain shared boundaries where appropriate so that even as the deep-brain model deforms to reflect intraoperative changes encoded in ioMRI, the subthalamic nucleus stays in contact with the substantia nigra, for example, while still providing a significantly sparser representation than the original volumetric atlas consisting of hundreds of millions of voxels. The …
Toward Real-Time, Robust Wearable Sensor Fall Detection Using Deep Learning Methods: A Feasibility Study, Haben Yhdego, Christopher Paolini, Michel Audette
Toward Real-Time, Robust Wearable Sensor Fall Detection Using Deep Learning Methods: A Feasibility Study, Haben Yhdego, Christopher Paolini, Michel Audette
Electrical & Computer Engineering Faculty Publications
Real-time fall detection using a wearable sensor remains a challenging problem due to high gait variability. Furthermore, finding the type of sensor to use and the optimal location of the sensors are also essential factors for real-time fall-detection systems. This work presents real-time fall-detection methods using deep learning models. Early detection of falls, followed by pneumatic protection, is one of the most effective means of ensuring the safety of the elderly. First, we developed and compared different data-segmentation techniques for sliding windows. Next, we implemented various techniques to balance the datasets because collecting fall datasets in the real-time setting has …
Dynamic Light Scattering Optical Coherence Tomography To Probe Motion Of Subcellular Scatterers., Nico J J Arezza, Marjan Razani, Michael C Kolios
Dynamic Light Scattering Optical Coherence Tomography To Probe Motion Of Subcellular Scatterers., Nico J J Arezza, Marjan Razani, Michael C Kolios
Medical Biophysics Publications
Optical coherence tomography (OCT) is used to provide anatomical information of biological systems but can also provide functional information by characterizing the motion of intracellular structures. Dynamic light scattering OCT was performed on intact, control MCF-7 breast cancer cells and cells either treated with paclitaxel to induce apoptosis or deprived of nutrients to induce oncosis. Autocorrelations (ACs) of the temporal fluctuations of OCT intensity signals demonstrate a significant decrease in decorrelation time after 24 h in both the paclitaxel-treated and nutrient-deprived cell groups but no significant differences between the two groups. The acquired ACs were then used as input for …
Logarithmic Intensity Compression In Fluorescence Guided Surgery Applications, Alisha V. Dsouza, Huiyun Lin, Jason Gunn, Brian W. Pogue
Logarithmic Intensity Compression In Fluorescence Guided Surgery Applications, Alisha V. Dsouza, Huiyun Lin, Jason Gunn, Brian W. Pogue
Dartmouth Scholarship
The use of fluorescence video imaging to guide surgery is rapidly expanding, and improvements in camera readout dynamic range have not matched display capabilities. Logarithmic intensity compression is a fast, single-step mapping technique that can map the useable dynamic range of high-bit fluorescence images onto the typical 8-bit display and potentially be a variable dynamic contrast enhancement tool. We demonstrate a ∼4.6 times improvement in image quality quantified by image entropy and a dynamic range reduction by a factor of ∼380 by the use of log-compression tools in processing in vivo fluorescence images.
Continuous Correction Of Differential Path Length Factor In Near-Infrared Spectroscopy, Tanveer Talukdar, Jason H. Moore, Solomon G. Diamond
Continuous Correction Of Differential Path Length Factor In Near-Infrared Spectroscopy, Tanveer Talukdar, Jason H. Moore, Solomon G. Diamond
Dartmouth Scholarship
In continuous-wave near-infrared spectroscopy (CW-NIRS), changes in the concentration of oxyhemoglobin and deoxyhemoglobin can be calculated by solving a set of linear equations from the modified Beer-Lambert Law. Cross-talk error in the calculated hemodynamics can arise from inaccurate knowledge of the wavelength-dependent differential path length factor (DPF). We apply the extended Kalman filter (EKF) with a dynamical systems model to calculate relative concentration changes in oxy- and deoxyhemoglobin while simultaneously estimating relative changes in DPF. Results from simulated and experimental CW-NIRS data are compared with results from a weighted least squares (WLSQ) method. The EKF method was found to effectively …
A Digital X-Ray Tomosynthesis Coupled Near Infrared Spectral Tomography System For Dual-Modality Breast Imaging, Venkataramanan Krishnaswamy, Kelly E. Michaelsen, Brian W. Pogue, Steven P. Poplack, Ian Shaw, Ken Defrietas, Ken Brooks, Keith D. Paulsen
A Digital X-Ray Tomosynthesis Coupled Near Infrared Spectral Tomography System For Dual-Modality Breast Imaging, Venkataramanan Krishnaswamy, Kelly E. Michaelsen, Brian W. Pogue, Steven P. Poplack, Ian Shaw, Ken Defrietas, Ken Brooks, Keith D. Paulsen
Dartmouth Scholarship
A Near Infrared Spectral Tomography (NIRST) system has been developed and integrated into a commercial Digital Breast Tomosynthesis (DBT) scanner to allow structural and functional imaging of breast in vivo. The NIRST instrument uses an 8-wavelength continuous wave (CW) laser-based scanning source assembly and a 75-element silicon photodiode solid-state detector panel to produce dense spectral and spatial projection data from which spectrally constrained 3D tomographic images of tissue chromophores are produced. Integration of the optical imaging system into the DBT scanner allows direct co-registration of the optical and DBT images, while also facilitating the synergistic use of x-ray contrast as …
Histogram Analysis Of Adc In Brain Tumor Patients, Debrup Banerjee, Jihong Wang, Jiang Li, Norbert J. Pelc (Ed.), Ehsan Samei (Ed.), Robert M. Nishikawa (Ed.)
Histogram Analysis Of Adc In Brain Tumor Patients, Debrup Banerjee, Jihong Wang, Jiang Li, Norbert J. Pelc (Ed.), Ehsan Samei (Ed.), Robert M. Nishikawa (Ed.)
Electrical & Computer Engineering Faculty Publications
At various stage of progression, most brain tumors are not homogenous. In this presentation, we retrospectively studied the distribution of ADC values inside tumor volume during the course of tumor treatment and progression for a selective group of patients who underwent an anti-VEGF trial. Complete MRI studies were obtained for this selected group of patients including pre- and multiple follow-up, post-treatment imaging studies. In each MRI imaging study, multiple scan series were obtained as a standard protocol which includes T1, T2, T1-post contrast, FLAIR and DTI derived images (ADC, FA etc.) for each visit. All scan series (T1, T2, FLAIR, …
Automated Classification Of Breast Pathology Using Local Measures Of Broadband Reflectance, Ashley M. Laughney, Venkataramanan Krishnaswamy, Pilar Beatriz Garcia-Allende, Olga M. Conde, Wendy A. Wells, Keith D. Paulsen, Brian W. Pogue
Automated Classification Of Breast Pathology Using Local Measures Of Broadband Reflectance, Ashley M. Laughney, Venkataramanan Krishnaswamy, Pilar Beatriz Garcia-Allende, Olga M. Conde, Wendy A. Wells, Keith D. Paulsen, Brian W. Pogue
Dartmouth Scholarship
We demonstrate that morphological features pertinent to a tissue's pathology may be ascertained from localized measures of broadband reflectance, with a mesoscopic resolution (100-μm lateral spot size) that permits scanning of an entire margin for residual disease. The technical aspects and optimization of a k-nearest neighbor classifier for automated diagnosis of pathologies are presented, and its efficacy is validated in 29 breast tissue specimens. When discriminating between benign and malignant pathologies, a sensitivity and specificity of 91 and 77% was achieved. Furthermore, detailed subtissue-type analysis was performed to consider how diverse pathologies influence scattering response and overall classification efficacy. The …
Image Guided Near-Infrared Spectroscopy Of Breast Tissue In Vivo Using Boundary Element Method, Subhadra Srinivasan, Colin M. Carpenter, Hamid R. Ghadyani, Senate J. Taka, Peter A. Kaufman, Roberta M. Diflorio-Alexander, Wendy A. Wells, Brian W. Pogue, Keith D. Paulsen
Image Guided Near-Infrared Spectroscopy Of Breast Tissue In Vivo Using Boundary Element Method, Subhadra Srinivasan, Colin M. Carpenter, Hamid R. Ghadyani, Senate J. Taka, Peter A. Kaufman, Roberta M. Diflorio-Alexander, Wendy A. Wells, Brian W. Pogue, Keith D. Paulsen
Dartmouth Scholarship
We demonstrate quantitative functional imaging using image-guided near-infrared spectroscopy (IG-NIRS) implemented with the boundary element method (BEM) for reconstructing 3-D optical property estimates in breast tissue in vivo. A multimodality MRI-NIR system was used to collect measurements of light reflectance from breast tissue. The BEM was used to model light propagation in 3-D based only on surface discretization in order to reconstruct quantitative values of total hemoglobin (HbT), oxygen saturation, water, and scatter. The technique was validated in experimental measurements from heterogeneous breast-shaped phantoms with known values and applied to a total of seven subjects comprising six healthy individuals …
Comparing Implementations Of Magnetic-Resonance-Guided Fluorescence Molecular Tomography For Diagnostic Classification Of Brain Tumors, Scott C. Davis, Kimberley S. Samkoe, Julia A. O’Hara, Summer L. Gibbs-Strauss, Keith D. Paulsen, Brian W. Pogue
Comparing Implementations Of Magnetic-Resonance-Guided Fluorescence Molecular Tomography For Diagnostic Classification Of Brain Tumors, Scott C. Davis, Kimberley S. Samkoe, Julia A. O’Hara, Summer L. Gibbs-Strauss, Keith D. Paulsen, Brian W. Pogue
Dartmouth Scholarship
Fluorescence molecular tomography (FMT) systems coupled to conventional imaging modalities such as magnetic resonance imaging (MRI) and computed tomography provide unique opportunities to combine data sets and improve image quality and content. Yet, the ideal approach to combine these complementary data is still not obvious. This preclinical study compares several methods for incorporating MRI spatial prior information into FMT imaging algorithms in the context of in vivo tissue diagnosis. Populations of mice inoculated with brain tumors that expressed either high or low levels of epidermal growth factor receptor (EGFR) were imaged using an EGF-bound near-infrared dye and a spectrometer-based MRI-FMT …
Automated Identification Of Tumor Microscopic Morphology Based On Macroscopically Measured Scatter Signatures, Pilar Beatriz Garcia-Allende, Venkataramanan Krishnaswamy, P Jack Hoopes, Kimberley S. Samkoe, Olga M. Conde, Brian W. Pogue
Automated Identification Of Tumor Microscopic Morphology Based On Macroscopically Measured Scatter Signatures, Pilar Beatriz Garcia-Allende, Venkataramanan Krishnaswamy, P Jack Hoopes, Kimberley S. Samkoe, Olga M. Conde, Brian W. Pogue
Dartmouth Scholarship
An automated algorithm and methodology is presented to identify tumor-tissue morphologies based on broadband scatter data measured by raster scan imaging of the samples. A quasi-confocal reflectance imaging system was used to directly measure the tissue scatter reflectance in situ, and the spectrum was used to identify the scattering power, amplitude, and total wavelength-integrated intensity. Pancreatic tumor and normal samples were characterized using the instrument, and subtle changes in the scatter signal were encountered within regions of each sample. Discrimination between normal versus tumor tissue was readily performed using a K-nearest neighbor classifier algorithm. A similar approach worked …
Receiver Operating Characteristic And Location Analysis Of Simulated Near-Infrared Tomography Images, Xiaomei Song, Brian W. Pogue, Hamid Dehghani, Shudong Jiang, Keith D. Paulsen, Tor D. Tosteson
Receiver Operating Characteristic And Location Analysis Of Simulated Near-Infrared Tomography Images, Xiaomei Song, Brian W. Pogue, Hamid Dehghani, Shudong Jiang, Keith D. Paulsen, Tor D. Tosteson
Dartmouth Scholarship
Receiver operating characteristic (ROC) analysis was performed on simulated near-infrared tomography images, using both human observer and contrast-to-noise ratio (CNR) computational assessment, for application in breast cancer imaging. In the analysis, a nonparametric approach was applied for estimating the ROC curves. Human observer detection of objects had superior capability to localize the presence of heterogeneities when the objects were small with high contrast, with a minimum detectable threshold of CNR near 3.0 to 3.3 in the images. Human observers were able to detect heterogeneities in the images below a size limit of 4 mm, yet could not accurately find the …
Using Pareto Fronts To Evaluate Polyp Detection Algorithms For Ct Colonography, Adam Huang, Jiang Li, Ronald M. Summers, Nicholas Petrick, Amy K. Hara
Using Pareto Fronts To Evaluate Polyp Detection Algorithms For Ct Colonography, Adam Huang, Jiang Li, Ronald M. Summers, Nicholas Petrick, Amy K. Hara
Electrical & Computer Engineering Faculty Publications
We evaluate and improve an existing curvature-based region growing algorithm for colonic polyp detection for our CT colonography (CTC) computer-aided detection (CAD) system by using Pareto fronts. The performance of a polyp detection algorithm involves two conflicting objectives, minimizing both false negative (FN) and false positive (FP) detection rates. This problem does not produce a single optimal solution but a set of solutions known as a Pareto front. Any solution in a Pareto front can only outperform other solutions in one of the two competing objectives. Using evolutionary algorithms to find the Pareto fronts for multi-objective optimization problems has been …
Hybrid Committee Classifier For A Computerized Colonic Polyp Detection System, Jiang Li, Jianhua Yao, Nicholas Petrick, Ronald M. Summers, Amy K. Hara, Joseph M. Reinhardt (Ed.), Josien P.W. Pluim (Ed.)
Hybrid Committee Classifier For A Computerized Colonic Polyp Detection System, Jiang Li, Jianhua Yao, Nicholas Petrick, Ronald M. Summers, Amy K. Hara, Joseph M. Reinhardt (Ed.), Josien P.W. Pluim (Ed.)
Electrical & Computer Engineering Faculty Publications
We present a hybrid committee classifier for computer-aided detection (CAD) of colonic polyps in CT colonography (CTC). The classifier involved an ensemble of support vector machines (SVM) and neural networks (NN) for classification, a progressive search algorithm for selecting a set of features used by the SVMs and a floating search algorithm for selecting features used by the NNs. A total of 102 quantitative features were calculated for each polyp candidate found by a prototype CAD system. 3 features were selected for each of 7 SVM classifiers which were then combined to form a committee of SVMs classifier. Similarly, features …
Contrast-Detail Analysis Characterizing Diffuse Optical Fluorescence Tomography Image Reconstruction, Scott C. Davis, Brian W. Pogue, Hamid Dehghani, Keith D. Paulsen
Contrast-Detail Analysis Characterizing Diffuse Optical Fluorescence Tomography Image Reconstruction, Scott C. Davis, Brian W. Pogue, Hamid Dehghani, Keith D. Paulsen
Dartmouth Scholarship
Contrast-detail analysis is used to evaluate the imaging performance of diffuse optical fluorescence tomography (DOFT), characterizing spatial resolution limits, signal-to-noise limits, and the trade-off between object contrast and size. Reconstructed images of fluorescence yield from simulated noisy data were used to determine the contrast-to-noise ratio (CNR). A threshold of CNR=3 was used to approximate a lowest acceptable noise level in the image, as a surrogate measure for human detection of objects. For objects 0.5 cm inside the edge of a simulated tissue region, the smallest diameter that met this criteria was approximately 1.7 mm, regardless of contrast level, and test …
Improved Quantification Of Small Objects In Near-Infrared Diffuse Optical Tomography, Subhadra Srinivasan, Brian W. Pogue, Hamid Dehghani, Shudong Jiang, Xiaomei Song, Keith D. Paulsen
Improved Quantification Of Small Objects In Near-Infrared Diffuse Optical Tomography, Subhadra Srinivasan, Brian W. Pogue, Hamid Dehghani, Shudong Jiang, Xiaomei Song, Keith D. Paulsen
Dartmouth Scholarship
Diffuse optical tomography allows quantification of hemoglobin, oxygen saturation, and water in tissue, and the fidelity in this quantification is dependent on the accuracy of optical properties determined during image reconstruction. In this study, a three-step algorithm is proposed and validated that uses the standard Newton minimization with Levenberg-Marquardt regularization as the first step. The second step is a modification to the existing algorithm using a two-parameter regularization to allow lower damping in a region of interest as compared to background. This second stage allows the recovery of the actual size of an inclusion. A region-based reconstruction is the final …