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Vikram Chalana

Publications and source records attributed to Vikram Chalana.

3 recordsLinked to original sources

Automatic Measurement of Ultrasound-Estimated Bladder Weight (UEBW) from Three-Dimensional Ultrasound.

Ultrasound-estimated bladder weight (UEBW) has the promise to become an important indicator for the diagnosis of bladder outlet obstruction. Our goal was to develop and evaluate an approach to accurately, consistently, conveniently, and noninvasively measure UEBW using three-dimensional (3D) ultrasound imaging. A 3D image of the bladder is acquired using a handheld ultrasound machine. The infravesical region of the bladder is delineated on this 3D data set to enable the calculation of bladder volume and the bladder surface area. The outer anterior wall of the bladder is delineated to enable the calculation of the bladder wall thickness. The UEBW is measured as a product of the bladder surface area, bladder wall thickness, and bladder muscle specific gravity. The UEBW was measured on 20 healthy male subjects and each subject was imaged several times at different bladder volumes to evaluate the consistency of the UEBW measurement. Our approach measured the average UEBW among healthy subjects to be 42 g (SD = 6 g). The UEBW was found to be fairly consistent with an average standard deviation of 4 g across a single subject at different bladder volumes between 200 mL and 400 mL. Our surface area measurements show that the bladder shape is significantly nonspherical.

Journal Article↗

Quantitative image analysis: software systems in drug development trials.

Multi-dimensional image analysis is being used increasingly to arrive at surrogate end-points for drug development trials. Various imaging modalities such as computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET) and ultrasound are used to analyze treatments for diseases such as cancer, multiple sclerosis, osteoarthritis, and Alzheimer's disease. However, extracting information from images can be tedious and is prone to high user variability. The medical image analysis community is moving towards advanced software systems specifically designed for drug development trials. These systems can automatically identify the anatomy of interest in medical images (segmentation methods), can compare the anatomy over time or between patients (registration methods) and allow the quantitative extraction of anatomical features and the integration of the data and results into a database management system, automatically tracking the changes made to the data (audit trail generation). In this article, we present a case study using a prototype system that is used for quantifying multiple sclerosis lesions from multivariate MRI.

Clinical Trials as Topic↗

Engineering and algorithm design for an image processing Api: a technical report on ITK--the Insight Toolkit.

We present the detailed planning and execution of the Insight Toolkit (ITK), an application programmers interface (API) for the segmentation and registration of medical image data. This public resource has been developed through the NLM Visible Human Project, and is in beta test as an open-source software offering under cost-free licensing. The toolkit concentrates on 3D medical data segmentation and registration algorithms, multimodal and multiresolution capabilities, and portable platform independent support for Windows, Linux/Unix systems. This toolkit was built using current practices in software engineering. Specifically, we embraced the concept of generic programming during the development of these tools, working extensively with C++ templates and the freedom and flexibility they allow. Software development tools for distributed consortium-based code development have been created and are also publicly available. We discuss our assumptions, design decisions, and some lessons learned.

Algorithms↗