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Proceedings of SPIE

Yuankai Huo, Shunxing Bao, Prasanna Parvathaneni, Bennett A Landman
Whole brain segmentation and cortical surface parcellation are essential in understanding the brain anatomical-functional relationship. Multi-atlas segmentation has been regarded as one of the leading segmentation methods for the whole brain segmentation. In our recent work, the multi-atlas technique has been adapted to surface reconstruction using a method called Multi-atlas CRUISE (MaCRUISE). The MaCRUISE method not only performed the consistent volume-surface analyses but also shown advantages on robustness compared with FreeSurfer method...
March 2018: Proceedings of SPIE
Shunxing Bao, Yuankai Huo, Prasanna Parvathaneni, Andrew J Plassard, Camilo Bermudez, Yuang Yao, Ilwoo Lyu, Aniruddha Gokhale, Bennett A Landman
When processing large medical imaging studies, adopting high performance grid computing resources rapidly becomes important. We recently presented a "medical image processing-as-a-service" grid framework that offers promise in utilizing the Apache Hadoop ecosystem and HBase for data colocation by moving computation close to medical image storage. However, the framework has not yet proven to be easy to use in a heterogeneous hardware environment. Furthermore, the system has not yet validated when considering variety of multi-level analysis in medical imaging...
March 2018: Proceedings of SPIE
Yuankai Huo, Zhoubing Xu, Shunxing Bao, Camilo Bermudez, Andrew J Plassard, Jiaqi Liu, Yuang Yao, Albert Assad, Richard G Abramson, Bennett A Landman
Spleen volume estimation using automated image segmentation technique may be used to detect splenomegaly (abnormally enlarged spleen) on Magnetic Resonance Imaging (MRI) scans. In recent years, Deep Convolutional Neural Networks (DCNN) segmentation methods have demonstrated advantages for abdominal organ segmentation. However, variations in both size and shape of the spleen on MRI images may result in large false positive and false negative labeling when deploying DCNN based methods. In this paper, we propose the Splenomegaly Segmentation Network (SSNet) to address spatial variations when segmenting extraordinarily large spleens...
March 2018: Proceedings of SPIE
Meg F Bobo, Shunxing Bao, Yuankai Huo, Yuang Yao, Jack Virostko, Andrew J Plassard, Ilwoo Lyu, Albert Assad, Richard G Abramson, Melissa A Hilmes, Bennett A Landman
Abdominal image segmentation is a challenging, yet important clinical problem. Variations in body size, position, and relative organ positions greatly complicate the segmentation process. Historically, multi-atlas methods have achieved leading results across imaging modalities and anatomical targets. However, deep learning is rapidly overtaking classical approaches for image segmentation. Recently, Zhou et al. showed that fully convolutional networks produce excellent results in abdominal organ segmentation of computed tomography (CT) scans...
March 2018: Proceedings of SPIE
Prasanna Parvathaneni, Ilwoo Lyu, Yuankai Huo, Justin Blaber, Allison E Hainline, Hakmook Kang, Neil D Woodward, Bennett A Landman
The choice of surface template plays an important role in cross-sectional subject analyses involving cortical brain surfaces because there is a tendency toward registration bias given variations in inter-individual and inter-group sulcal and gyral patterns. In order to account for the bias and spatial smoothing, we propose a feature-based unbiased average template surface. In contrast to prior approaches, we factor in the sample population covariance and assign weights based on feature information to minimize the influence of covariance in the sampled population...
March 2018: Proceedings of SPIE
Ilwoo Lyu, Hakmook Kang, Neil D Woodward, Bennett A Landman
Sulcal depth is an important marker of brain anatomy in neuroscience/neurological function. Previously, sulcal depth has been explored at the region-of-interest (ROI) level to increase statistical sensitivity to group differences. In this paper, we present a fully automated method that enables inferences of ROI properties from a sulcal region-focused perspective consisting of two main components: 1) sulcal depth computation and 2) sulcal curve-based refined ROIs. In conventional statistical analysis, the average sulcal depth measurements are employed in several ROIs of the cortical surface...
March 2018: Proceedings of SPIE
Allison E Hainline, Vishwesh Nath, Prasanna Parvathaneni, Justin Blaber, Baxter Rogers, Allen Newton, Jeffrey Luci, Heidi Edmonson, Hakmook Kang, Bennett A Landman
An understanding of the bias and variance of diffusion weighted magnetic resonance imaging (DW-MRI) acquisitions across scanners, study sites, or over time is essential for the incorporation of multiple data sources into a single clinical study. Studies that combine samples from various sites may be introducing confounding due to site-specific artifacts and patterns. Differences in bias and variance across sites may render the scans incomparable, and, without correction, any inferences obtained from these data are misleading...
March 2018: Proceedings of SPIE
Vishwesh Nath, Kurt G Schilling, Allison E Hainline, Prasanna Parvathaneni, Justin A Blaber, Ilwoo Lyu, Adam W Anderson, Hakmook Kang, Allen T Newton, Baxter P Rogers, Bennett A Landman
High Angular Resolution Diffusion Imaging (HARDI) models are used to capture complex intra-voxel microarchitectures. The magnetic resonance imaging sequences that are sensitized to diffusion are often highly accelerated and prone to motion, physiologic, and imaging artifacts. In diffusion tensor imaging, robust statistical approaches have been shown to greatly reduce these adverse factors without human intervention. Similar approaches would be possible with HARDI methods, but robust versions of each distinct HARDI approach would be necessary...
March 2018: Proceedings of SPIE
Shikha Chaganti, Bennett A Landman
Image registration involves identification of a transformation to fit a target image to a reference image space. The success of the registration process is vital for correct interpretation of the results of many medical image-processing applications, including multi-atlas segmentation. While there are several validation metrics employed in rigid registration to examine the accuracy of the method, non-rigid registrations (NRR) are validated subjectively in most cases, validated in offline cases, or based on image similarity metrics, all of which have been shown to poorly correlate with true registration quality...
March 2018: Proceedings of SPIE
Camilo Bermudez, Andrew J Plassard, Taylor L Davis, Allen T Newton, Susan M Resnick, Bennett A Landman
An important task in image processing and neuroimaging is to extract quantitative information from the acquired images in order to make observations about the presence of disease or markers of development in populations. Having a low-dimensional manifold of an image allows for easier statistical comparisons between groups and the synthesis of group representatives. Previous studies have sought to identify the best mapping of brain MRI to a low-dimensional manifold, but have been limited by assumptions of explicit similarity measures...
March 2018: Proceedings of SPIE
Baxter P Rogers, Justin Blaber, Allen T Newton, Colin B Hansen, E Brian Welch, Adam W Anderson, Jeffrey J Luci, Carlo Pierpaoli, Bennett A Landman
Gradient coils in magnetic resonance imaging do not produce perfectly linear gradient fields. For diffusion imaging, the field nonlinearities cause the amplitude and direction of the applied diffusion gradients to vary over the field of view. This leads to site- and scan-specific systematic errors in estimated diffusion parameters such as diffusivity and anisotropy, reducing reliability especially in studies that take place over multiple sites. These errors can be substantially reduced if the actual scanner-specific gradient coil magnetic fields are known...
March 2018: Proceedings of SPIE
Andreea Dimofte, Jarod Finlay, Yi Hong Ong, Timothy C Zhu
Successful outcome of Photodynamic therapy (PDT) depends on accurate delivery of prescribed light dose. A quality assurance program is necessary to ensure that light dosimetry is correctly measured. We have instituted a QA program that include examination of long term calibration uncertainty of isotropic detectors for light fluence rate, power meter head intercomparison for laser power, stability of the light-emitting diode (LED) light source integrating sphere as a light fluence standard, laser output and calibration of in-vivo reflective fluorescence and absorption spectrometers...
March 2018: Proceedings of SPIE
Yi Hong Ong, Jonah Padawer-Curry, Jarod C Finlay, Michele M Kim, Andreea Dimofte, Keith Cengel, Timothy C Zhu
PDT efficacy depends on the concentration of photosensitizer, oxygen, and light delivery in patient tissues. In this study, we measure the in-vivo distribution of important dosimetric parameters, namely the tissue optical properties (absorption μa ( λ ) and scattering μs ' ( λ ) coefficients), photofrin concentration ( c photofrin ), blood oxygen saturation (%St O2 ), and total hemoglobin concentration (THC), before and after PDT. We characterize the inter- and intra-patient heterogeneity of these quantities and explore how these properties change as a result of PDT treatment...
March 2018: Proceedings of SPIE
Liqiang Ren, Cynthia H McCollough, Lifeng Yu
In order to perform material decomposition for a three-material mixture, dual-energy CT (DECT) has to incorporate an additional condition, typically the prior information related to certain physical constraints such as volume or mass conservation. With the introduction of photon-counting CT and other multi-energy CT (MECT) platform, more than 2 energy bins can be simultaneously acquired, which in principle can solve a three-material problem without the need of additional prior information. The purpose of this work was to investigate the impact of prior information on noise and bias properties of three-material decomposition in both DECT and MECT, and to evaluate if the prior information is still needed in MECT...
March 2018: Proceedings of SPIE
Steven Tilley, Wojciech Zbijewski, Jeffrey H Siewerdsen, J Webster Stayman
Material decomposition in CT has the potential to reduce artifacts and improve quantitative accuracy by utilizing spectral models and multi-energy scans. In this work we present a novel Model-Based Material Decomposition (MBMD) method based on an existing iterative reconstruction algorithm derived from a general non-linear forward model. A digital water phantom with inserts containing different concentrations of calcium was scanned on a kV switching system. We used the presented method to simultaneously reconstruct water and calcium material density images, and compared the results to an image domain and a projection domain decomposition method...
March 2018: Proceedings of SPIE
Hao Zhang, Grace J Gang, Hao Dang, Marc S Sussman, Cheng Ting Lin, Jeffrey H Siewerdsen, J Webster Stayman
Purpose: Prior-image-based reconstruction (PIBR) is a powerful tool for low-dose CT, however, the nonlinear behavior of such approaches are generally difficult to predict and control. Similarly, traditional image quality metrics do not capture potential biases exhibited in PIBR images. In this work, we identify a new bias metric and construct an analytical framework for prospectively predicting and controlling the relationship between prior image regularization strength and this bias in a reliable and quantitative fashion...
March 2018: Proceedings of SPIE
Aniket A Tolpadi, Maureen L Stone, Aaron Carass, Jerry L Prince, Arnold D Gomez
The tongue's deformation during speech can be measured using tagged magnetic resonance imaging, but there is no current method to directly measure the pattern of muscles that activate to produce a given motion. In this paper, the activation pattern of the tongue's muscles is estimated by solving an inverse problem using a random forest. Examples describing different activation patterns and the resulting deformations are generated using a finite-element model of the tongue. These examples form training data for a random forest comprising 30 decision trees to estimate contractions in 262 contractile elements...
February 2018: Proceedings of SPIE
Venkata S Arikatla, Mohit Tyagi, Andinet Enquobahrie, Tung Nguyen, George H Blakey, Ray White, Beatriz Paniagua
Surgical simulators are powerful tools that assist in providing advanced training for complex craniofacial surgical procedures and objective skills assessment such as the ones needed to perform Bilateral Sagittal Split Osteotomy (BSSO). One of the crucial steps in simulating BSSO is accurately cutting the mandible in a specific area of the jaw, where surgeons rely on high fidelity visual and haptic cues. In this paper, we present methods to simulate drilling and cutting of the bone using the burr and the motorized oscillating saw respectively...
February 2018: Proceedings of SPIE
Hao Gong, Lifeng Yu, Shuai Leng, Samantha Dilger, Wei Zhou, Liqiang Ren, Cynthia H McCollough
Channelized Hotelling observer (CHO) has demonstrated strong correlation with human observer (HO) in both single-slice viewing mode and multi-slice viewing mode in low-contrast detection tasks with uniform background. However, it remains unknown if the simplest single-slice CHO in uniform background can be used to predict human observer performance in more realistic tasks that involve patient anatomical background and multi-slice viewing mode. In this study, we aim to investigate the correlation between CHO in a uniform water background and human observer performance at a multi-slice viewing mode on patient liver background for a low-contrast lesion detection task...
February 2018: Proceedings of SPIE
Zhenyu Xiong, Sarath Vijayan, Chao Guo, Stephen Rudin, Daniel R Bednarek
The purpose of this study was to evaluate the effect of patient head size on radiation dose to radiosensitive organs, such as the eye lens, brain and spinal cord in fluoroscopically guided neuro-interventional procedures and CBCT scans of the head. The Toshiba Infinix C-Arm System was modeled in BEAMnrc/EGSnrc Monte-Carlo code and patient organ and effective doses were calculated in DOSxynrc/EGSnrc for CBCT and interventional procedures. X-ray projections from different angles, CBCT scans, and neuro-interventional procedures were simulated on a computational head phantom for the range of head sizes in the adult population and for different pediatric ages...
February 2018: Proceedings of SPIE
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