A Neural Network Approach for classifying TACS By Mike Smith.

Slides:

Advertisements

Similar presentations

Detection and Measurement of Pavement Cracking Bagas Prama Ananta.

Advertisements

Digital Photography By Mike Volker. What is Digital Photography? A form of Photography that uses digital technology to make images of subjects Replaced.

Scanning Confocal Basics n What’s so special ? n Confocals give higher resolution than normal microscopes. n Confocals can OPTICALLY SECTION a sample.

Breast Cancer ECM Visualization using Multiphoton Imaging Jeremy Bredfeldt LOCI, Morgridge Institute for Research.

Automatic in vivo Microscopy Video Mining for Leukocytes * Chengcui Zhang, Wei-Bang Chen, Lin Yang, Xin Chen, John K. Johnstone.

The Dependence of the Apparent Diffusion Coefficient on Voxel Location and Calculation Method Lars Ewell 1, Naren Vijayakumar Meeting of the American.

New Techniques in Computational photography Marc Levoy Computer Science Department Stanford University.

A 3D Approach for Computer-Aided Liver Lesion Detection Reed Tompkins DePaul Medix Program 2008 Mentor: Kenji Suzuki, Ph.D. Special Thanks to Edmund Ng.

(Semi)Automatic Quantification of the Internal Elastic Lamina Fenestrae in Remodeling Arteries A Feasibility Study Master Thesis Harald Groen.

Types of Microscopes Microscopes Rule!!!!!!!!!!. There are four basic kinds of microscopes: Optical (or light) Electron Scanning Probe Ion.

Direct Digital Radiography or Direct Capture Radiography Bushong Ch. 27.

Anti Virus Techniques Jordan & Ryan Use of Checksum The Binary for key files is added up to a number especially in the boot files When these files are.

Dual Wedge Confocal Microscope Christopher Carr Thomas Aites Christopher Marinis Jeffrey Guziejka.

Optical Microscopy Widefield Microscopy - Brightfield, Darkfield, DIC, Phase Contrast, Fluorescence … Total Internal Reflection (TIR and TIRF) Microscopy.

LLNL-PRES This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under contract.

ENDA MOLLOY, ELECTRONIC ENG. FINAL PRESENTATION, 31/03/09. Automated Image Analysis Techniques for Screening of Mammography Images.

Kunal Mitra Professor, Mechanical and Aerospace Engineering Department Director- Biomedical Engineering Program Florida Institute of Technology, Melbourne,

An Example of Course Project Face Identification.

Real-time Robotic Radiation Oncology Brian Murphy Electronic and Computer Engineering NUI Galway.

Brain-Computer-Interface for Stress Detection Hassan Farooq, Ilona Wong Supervisor: Steve Mann Administrator: Cristiana Amza Section 8 Collecting Brainwave.

Mike Newchurch 1, Shi Kuang 1, John Burris 2, Steve Johnson 3, Stephanie Long 1 1 University of Alabama in Huntsville, 2 NASA/Goddard Space Flight Center,

DIGITAL IMAGE PROCESING NASA LUNAR AND PLANETARY EXPLORATION.

Christopher Mitchell The Cooper Union Fluorescent Microscopy, Eigenobjects, and the Cellular Density Project Christopher Mitchell The Cooper Union Stevens.

Arbitrary and Dynamic Patterning in a Programmable Array Microscope

Optics Focus Dr. Marvin Minsky Confocal microscope: 1957.

Phase calibration pictures 3/9/10. Dark count image Required for: 1. determining image intensity in the absence of light. 2. also required for phase artifact.

 Science is our knowledge of all the living and nonliving things around us.  Technology is the application of scientific knowledge to solve human needs.

Work Package 2 – Overview of instrumentation, data gathering and calibration issues Calibration of the Galileo 94GHz radar – two years of data Nicolas.

Direct Digital Radiography or Direct Capture Radiography

Designing a Microscopy Experiment Kurt Thorn, PhD Director, Image from Susanne Rafelski, Marshall lab.

Date of download: 6/27/2016 Copyright © 2016 SPIE. All rights reserved. Experimental setup for 3-D vision of the foot sole. Figure Legend: From: Computer.

Simulated GOLD Observations of Atmospheric Waves

Face Detection EE368 Final Project Group 14 Ping Hsin Lee

HyperNetworks Engın denız usta

CS201 Lecture 02 Computer Vision: Image Formation and Basic Techniques

Visualizing Dendritic Cell Networks In vivo

Optical Coherence Tomography

AF647-RIS is internalized by TAMs in vivo.

Week 6 Cecilia La Place.

Meteorological Service of Canada

Non-linear hypotheses

Bell Work Write down the following terms on a blank sheet of paper.

Maximally Stable Extremal Regions

Combining Geometric- and View-Based Approaches for Articulated Pose Estimation David Demirdjian MIT Computer Science and Artificial Intelligence Laboratory.

A, baseline and 4-week PET scan from patient 2 (MET c

Longitudinal imaging after initial diagnosis

Applications of Cellular Neural Networks to Image Understanding

A radio image of Messier 87 (M87), a giant elliptical galaxy in the Virgo Cluster by the Very Large Array (VLA), and an image of the center section by.

Example of pretreatment (A and B) and 8-week posttreatment (C and D) PET CT images. Example of pretreatment (A and B) and 8-week posttreatment (C and D)

Visualization of computational image feature descriptors.

Fig. 5. MasSpec Pen analysis of an HGSC tissue sample with mixed histologic composition. MasSpec Pen analysis of an HGSC tissue sample with mixed histologic.

Pure Research: Biosensing Plasmonic Devices

Presentation by: Lillian Lau

The Image The pixels in the image The mask The resulting image 255 X

John Condeelis, Jeffrey W. Pollard Cell

ADC imaging. ADC imaging. A, Delineation of the ROI (left, green limits), intensity versus b value graph of a representative pixel (right), and a parametric.

Computed tomographic images from a patient with BRAFL597S-mutant metastatic melanoma responding to therapy with the MEK inhibitor TAK-733. Computed tomographic.

Using FPGA to Provide Faster Digitally Enhanced Images in Order to Demonstrate a More Efficient Way to Process Images When Compared to Using Software.

Using CLARITY to clear and image other organs.

Volume 15, Issue 11, Pages (June 2016)

New developments in artifical intelligence dr. Marc B. I

Expression pattern of TLR-4 and MyD88 in EOC cells.

Intraoperative visualization of the tumor microenvironment and quantification of extracellular vesicles by label-free nonlinear imaging by Yi Sun, Sixian.

HGSOC mutational processes are established early and are patient-specific. HGSOC mutational processes are established early and are patient-specific. A,

PVT1 facilitated gastric cancer progression in a FOXM1-mediated manner

A, Selected 4 quantitative imaging features significantly associated with 3 imaging subtypes, including tumor volume, tumor sphericity, tumor homogeneity.

Vorozole treatment-associated changes in protein abundance of multiple antigens. Vorozole treatment-associated changes in protein abundance of multiple.

Detection of microcalcifications in 4T1 mammary tumors and human breast tumor tissue. Detection of microcalcifications in 4T1 mammary tumors and human.

CD36 expression is coordinately regulated in multiple cellular compartments. CD36 expression is coordinately regulated in multiple cellular compartments.

CD36 expression in tissue adjacent and distal to the tumor.

Presentation transcript:

A Neural Network Approach for classifying TACS By Mike Smith

Personal Background ECE Master’s student Research Assistant for the Laboratory for Optical and Computational Instrumentation (LOCI) –Design Control System for Laser Scanning Microscopes

Project Overview Classifying TACS (Tumor Associated Collagen Signatures) –Change in density and alignment during tumor development –Signatures can be seen before a tumor is formed allowing for early detection of cancer

Data Gathering Data is gathered using multiphoton laser scanning microscope Collagen produces a second harmonic effect naturally –Basically shine a laser on collagen, it will glow and we can capture that and form an image

Training/Testing Data -Classified data from images of tumors from a mouse mammary -Broken up into 32x32 discrete chunks

Current Techniques Classify intensity or average intensity of a section of data using artificial neural networks –Naive approach –Haven’t been happy with results –Gives baseline though Classify based on change in intensity and consistency with areas around it

Future Work Classify based on raw data, not images –Only 8 bit pixels, ADC provides 12 bit resolution Try to predict signatures before tumor is formed -Early Cancer Detection

References P. P. Provenzano, et al., "Collagen reorganization at the tumor-stromal interface facilitates local invasion". BMC Med. 4, 38 (2006).