Alexandra Lauric

alauri02@eecs.tufts.edu

 

 

 

I am a fifth-year PhD student at Tufts University, Department of Computer Science.

 

My main interests are Computer Vision and Computational Geometry and my research area is medical imaging. I currently work on automatic detection and shape analysis of intracranial aneurysm. My advisors are Prof. Eric Miller and Prof. Sarah Frisken. We work in collaboration with Dr. Adel Malek from Tufts Medical Center, Department of Neurosurgery.

 

Research links:

 

My work

 

Computer Graphics at Tufts

Computer Graphics research group web page.

 

Computational Geometry at Tufts

Computational Geometry research group web page.

 

The Visible Human Project

In 1989, the National Library of Medicine (NLM) started The Visible Human Project with the goal of creating a digital atlas of the human body. In 1991, full CT and MRI data sets were collected of a fresh cadaver (39-year old convicted murderer Joseph Paul Jernigan). Physical sections of the cadaver were also collected and photographed at high resolution. In 1995, CT, MRI and RGB photos were collected of the fresh cadaver of a 59-year-old Maryland woman who donated her body to science. See the project web page.

 

The National Alliance for Medical Imaging Computing (NA-MIC)

A multi-institutional, interdisciplinary team of computer scientists, software engineers, and medical investigators who develop computational tools for the analysis and visualization of medical image data. The purpose of the center is to provide the infrastructure and environment for the development of computational algorithms and open source technologies, and then oversee the training and dissemination of these tools to the medical research community.

 

Bill Lorensen: Marching Through the Visible Man

Experiments done at GE research lab with the fresh CT data set. A guide on using VTK to extract skin, bone, muscle and bowels from the Visible Man data set.

 

Human Anatomy Online

Animations, hundreds of graphics and thousands of descriptive links to study the anatomy of the human body.  Ideal reference site to find out more about the medical description used by doctors.

 

Open Source tools to process, analyze and visualize medical images:

 

ITK - Insight Segmentation and Registration Toolkit

A powerful open-source software toolkit for performing registration and segmentation. Segmentation is the process of identifying and classifying data found in a digitally sampled representation. Typically the sampled representation is an image acquired from such medical instrumentation as CT or MRI scanners. Registration is the task of aligning or developing correspondences between data. For example, in the medical environment, a CT scan may be aligned with a MRI scan in order to combine the information contained in both. See my guide on how to install ITK and VTK.

 

VTK - Visualization Toolkit

An open source, freely available software system for 3D computer graphics, image processing, and visualization. VTK supports a wide variety of visualization algorithms including scalar, vector, tensor, texture, and volumetric methods; and advanced modeling techniques such as implicit modeling, polygon reduction, mesh smoothing, cutting, contouring, and Delaunay triangulation. VTK consists of a C++ class library, and several interpreted interface layers including Tcl/Tk, Java, and Python. See my guide on how to install ITK and VTK.

 

VolView

An intuitive and interactive system for volume visualization. VolView is a commercial product, but a restricted version is available for free. I use it to visualize the results of my ITK scripts.

 

ParaView

An open-source, multi-platform, extensible application designed for visualizing large data sets. I use it to visualize the 3D models I create with VTK.

 

DicomWorks

A free DICOM viewer and converter dedicated to people working with DICOM files. DiacomWorks is used to view volumes consisting of a series of 2D images.

DICOM is a file format introduced by the American College of Radiology (ACR) and National Electrical Manufacturers Association (NEMA) as a standard medical image format. A basic DICOM file contains a header and a data set. The header consists of a 128 byte and contains information about the data set: voxel size, orientation, series number, image number. DicomWorks displays the data set of each 2D image and it gives the user easy access to the header information.

 

3D Slicer

The 3D Slicer is freely available, open-source software for visualization, registration, segmentation, and quantification of medical data. Slicer integrates several facets of image-guided medicine into a single environment. It provides capabilities for automatic registration (aligning data sets), semi-automatic segmentation (extracting structures such as vessels and tumors from the data), generation of 3D surface models (for viewing the segmented structures), 3D visualization, and quantitative analysis (measuring distances, angles, surface areas, and volumes) of various medical scans.

 

Books:

·        Insight into Images: Principles and Practice for Segmentation, Registration, and Image Analysis

·         The ITK Software Guide: The Insight Segmentation and Registration Toolkit (version 1.4)

·        The Visualization Toolkit, Third Edition

 

Other links:

 

How to install ITK and VTK

A step by step guide on how to download and install ITK and VTK on Windows machines. Learn from my mistakes.

 

List of the classes I have taken so far.