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Tomography Computed Bioengineering 280A Principles of Biomedical Imaging Fall Quarter 2007 CT Lecture 1 TT Liu, BE280A, UCSD Fall 2007 TT Liu, BE280A, UCSD Fall 2007 Suetens 2002 Computed Tomography Fan Beam Scanner Generations Parallel Beam TT Liu, BE280A, UCSD Fall 2007 Suetens 2002 TT Liu, BE280A, UCSD Fall 2007 Suetens 2002 1 Single vs. Multi-slice TT Liu, BE280A, UCSD Fall 2007 From http://www.sprawls.org/resources/CTIMG/classroom.htm TT Liu, BE280A, UCSD Fall 2007 Suetens 2002 Scanner Generations 1G vs. 2G scanner Example 6.1 from Prince and Links. Compare 1G vs. 2G scanner whose source - detector apparatus can move linearly at speed of 1 m/sec; FOV 0.5m; 360 projections over 180 degrees; 0.5 s for apparatus to rotate one angular increment, regardless of angle. Question : Scan time for 1 G scanner? Scan time for 2G scanner with 9 detectors space 0.5 degrees apart? Answer : 1G scanner : 0.5m/(1m/s) = 0.5s per projection. 360 * 0.5 = 180s scan time 360 * 0.5 = 180s for rotation of apparatus. Total time = 360 s or 6 minutes. 2G scanner : Required angular resolution is 180/360 = 0.5 degrees - - agrees with spacing. 360/9 = 40 rotations required. 40 * 0.5 = 20s for scanning 40 * 0.5 = 20s for rotations. Total time = 40s. TT Liu, BE280A, UCSD Fall 2007 Prince and Links 2005 ! TT Liu, BE280A, UCSD Fall 2007 2 3G, 6G, and 7G scanners 3G scanner : Typical scanner acquires 1000 projections with fanbeam angle of 30 to 60 degrees; 500 to 700 detectors; 1 to 20 seconds. 6G : Spiral/Helical CT 60 cm torso scan : 30s. 24 cm lung scan : 12s 15 cm angio : 30s 7G : Multislice CT 64 or more parallel 1D projections. ! TT Liu, BE280A, UCSD Fall 2007 TT Liu, BE280A, UCSD Fall 2007 Suetens 2002 Detectors Id = CT Line Integral " E max 0 S0 ( E ) E exp # " ( s; E $)ds dE 0 ( d ) Monoenergetic Approximation Id = I0 exp # " ( s;E )ds 0 ( d ) %I ( gd = #log' d * & I0 ) = Prince and Links 2005 " (s;E )ds 0 d TT Liu, BE280A, UCSD Fall 2007 TT Liu, BE280A, UCSD Fall 2007 ! 3 CT Number CT_number = CT Display " water #1000 water Measured in Houns eld Units (HU) Air: -1000 HU ! Soft Tissue: -100 to 60 HU Cortical Bones: 250 to 1000 HU Metal and Contrast Agents: > 2000 HU TT Liu, BE280A, UCSD Fall 2007 TT Liu, BE280A, UCSD Fall 2007 Suetens 2002 Direct Inverse Approach 1 3 p3 Direct Inverse Approach 0%" 1 % '$ ' 1'$ 2 ' 0'$ 3 ' '$ ' 1&# 4 & 2 4 p4 p1 p2 p1= 1+ 2 p2= 3+ 4 p3= 1+ 3 p4= 2+ 4 " p1 % "1 $'$ $ p2 ' = $0 $ p3 ' $1 $'$ # p4 & #0 1 0 0 1 0 1 1 0 1 3 p3 2 4 p4 p1 p2 p1= 1+ 2 p2= 3+ 4 p3= 1+ 3 p4= 2+ 4 " p1 % "1 $'$ $ p2 ' = $0 $ p3 ' $1 $'$ # p4 & #0 1 0 0 1 0 1 1 0 0%" 1 % '$ ' 1'$ 2 ' 0'$ 3 ' '$ ' 1&# 4 & 4 equations, 4 unknowns. ! Are these the correct equations to use? No, equations are not linearly independent. p1+ p4= p2- p3 Matrix is not full rank. TT Liu, BE280A, UCSD Fall 2007 4 equations, 4 unknowns. ! Are these the correct equations to use? No, equations are not linearly independent. p4= p1+ p2- p3 Matrix is not full rank. TT Liu, BE280A, UCSD Fall 2007 4 Direct Inverse Approach 1 3 p3 Iterative Inverse Approach Algebraic Reconstruction Technique (ART) 0%" 1 % '$ ' 1'$ 2 ' 0'$ 3 ' '$ ' 1&# 4 & 2 4 p4 p1 p2 p5 p1= 1+ 2 p2= 3+ 4 p3= 1+ 3 p5= 1+ 4 " p1 % "1 $'$ $ p2 ' = $0 $ p3 ' $1 $'$ # p5 & #1 1 0 0 0 0 1 1 0 1 3 4 2 4 6 3 7 5 2.5 2.5 2.5 2.5 5 5 4 equations, 4 unknowns. These are linearly independent now. 2 In general for a NxN image, N! unknowns, N2 equations. This requires the inversion of a N2xN2 matrix For a high-resolution 512x512 image, N2=262144 equations. Requires inversion of a 262144x262144 matrix! Inversion process sensitive to measurement errors. 1 3 5 2 4 5 3 7 1.5 3.5 5 1.5 3.5 5 3 7 TT Liu, BE280A, UCSD Fall 2007 TT Liu, BE280A, UCSD Fall 2007 Backprojection 000 030 000 3 0 30 0 3 0 3 In-Class Exercise 1 3 8.2 2 4 8.8 5.7 11.3 10.1 000 111 000 100 121 001 110 131 011 111 141 111 TT Liu, BE280A, UCSD Fall 2007 Suetens 2002 TT Liu, BE280A, UCSD Fall 2007 Suetens 2002 5 Projections "r% " cos( sin( %" x% $ '=$ '$ ' #s& #)sin( cos(&# y& "x% "cos( )sin(%"r% $ '=$ '$ ' #y& #sin( cos( &#s& Projections % ( I(r,") = I0 exp'# $ (x, y)ds* & Lr ," ) % ( = I0 exp'# $ (r cos" # ssin",r sin" + scos")ds* & Lr ," ) TT Liu, BE280A, UCSD Fall 2007 ! TT Liu, BE280A, UCSD Fall 2007 Suetens 2002 Suetens 2002 ! Projections % ( I(r,") = I0 exp'# $ L (r cos" # ssin",r sin" + scos")ds* & ) r ," Radon Transform g(r,") = p(r,") = #ln ! I" (r) I0 = $ L r ," (r cos" # ssin",r sin" + scos")ds % (x(s), y(s))ds = % (r cos" # ssin",r sin" + scos")ds = % % (x, y)& ( x cos" + y sin" # r)dxdy #$ $ #$ $ $ #$ #$ $ ! ! r r " ! r z r rr z =r r ( xx + yy ) (cos"x + sin"y ) = r x cos" + y sin" = r ! TT Liu, BE280A, UCSD Fall 2007 Suetens 2002 TT Liu, BE280A, UCSD Fall 2007 ! ! 6 Example #1 x 2 + y 2 " 1 f (x, y) = $ %0 otherwise g(l," = 0) = = Sinogram ! % $ #$ f (l, y)dy % 1#l 2 # 1#l 2 dy l &1 otherwise '2 1# l 2 ) =( ) *0 ! TT Liu, BE280A, UCSD Fall 2007 TT Liu, BE280A, UCSD Fall 2007 Suetens 2002 y Backprojection x x0 Backprojection b(x, y) = B{ p( l," )} = b(x 0 , y) = p( l," = 0)#" = p(x 0 ,0)#" ! $ # 0 p(x cos" + y sin",")d" ! l b" (x, y) = g(x cos" + y sin",")#" b(x, y) = B{g( l," )} ! TT Liu, BE280A, UCSD Fall 2007 = $ # 0 g(x cos" + y sin",")d" Suetens 2002 TT Liu, BE280A, UCSD Fall 2007 Suetens 2002 ! 7 Backprojection Example b(x, y) = B{ p( l," )} = $ # 0 p(x cos" + y sin",")d" ! TT Liu, BE280A, UCSD Fall 2007 Suetens 2002 TT Liu, BE280A, UCSD Fall 2007 Prince & Links 2006 8
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UCSD >> BE >> 280 (Fall, 2008)
Topics Projection Slice Theorem Fourier Transforms Bioengineering 280A Principles of Biomedical Imaging Fall Quarter 2007 CT/Fourier Lecture 2 TT Liu, BE280A, UCSD Fall 2007 TT Liu, BE280A, UCSD Fall 2007 Projection Slice Theorem G(\",#) = The ...
UCSD >> BE >> 280 (Fall, 2008)
Topics Modulation Transfer Function Convolution/Multiplication Modulation Revisit Projection-Slice Theorem Filtered Backprojection Bioengineering 280A Principles of Biomedical Imaging Fall Quarter 2007 CT/Fourier Lecture 3 TT Liu, BE280A, UCSD...
UCSD >> BE >> 280 (Fall, 2008)
Topics Sampling Requirements in CT Sampling Theory Aliasing Bioengineering 280A Principles of Biomedical Imaging Fall Quarter 2007 CT/Fourier Lecture 4 TT Liu, BE280A, UCSD Fall 2007 TT Liu, BE280A, UCSD Fall 2007 CT Sampling Requirements What...
UCSD >> BE >> 280 (Fall, 2008)
Topics The concept of spin Precession of magnetic spin Relaxation Bloch Equation Bioengineering 280A Principles of Biomedical Imaging Fall Quarter 2007 MRI Lecture 1 TT. Liu, BE280A, UCSD Fall 2007 TT. Liu, BE280A, UCSD Fall 2007 Spin Intrin...
UCSD >> BE >> 280 (Fall, 2008)
Gradients Spins precess at the Larmor frequency, which is proportional to the local magnetic eld. In a constant magnetic eld Bz=B0, all the spins precess at the same frequency (ignoring chemical shift). Bioengineering 280A Principles of Biomedical I...
UCSD >> BE >> 280 (Fall, 2008)
Fourier Sampling Bioengineering 280A Principles of Biomedical Imaging Fall Quarter 2007 MRI Lecture 3 Instead of sampling the signal, we sample its Fourier Transform ? F Sample F-1 Thomas Liu, BE280A, UCSD, Fall 2007 Thomas Liu, BE280A, UCSD, Fal...
UCSD >> BE >> 280 (Fall, 2008)
Static Inhomogeneities In the ideal situation, the static magnetic eld is totally uniform and the reconstructed object is determined solely by the applied gradient elds. In reality, the magnet is not perfect and will not be totally uniform. Part of t...
UCSD >> BE >> 280 (Fall, 2008)
RF Excitation Bioengineering 280A Principles of Biomedical Imaging Fall Quarter 2007 MRI Lecture 4 Thomas Liu, BE280A, UCSD, Fall 2007 Thomas Liu, BE280A, UCSD, Fall 2007 From Levitt, Spin Dynamics, 2001 RF Excitation At equilibrium, net magnet...
UCSD >> BE >> 280 (Fall, 2008)
Moving Spins So far we have assumed that the spins are not moving (aside from thermal motion giving rise to relaxation), and contrast has been based upon T1, T2, and proton density. We were able to achieve different contrasts by adjusting the appropr...
UCSD >> BE >> 280 (Fall, 2008)
Bioengineering 280A Principles of Biomedical Imaging Fall Quarter 2007 Ultrasound Lecture 1 Sonosite 180 From Suetens 2002 Acuson Sequoia TT Liu, BE280A, UCSD, Fall 2007 TT Liu, BE280A, UCSD, Fall 2007 Basic System Basic System Echo occurs at...
UCSD >> BE >> 280 (Fall, 2008)
Single-slit Diffraction Bioengineering 280A Principles of Biomedical Imaging Fall Quarter 2007 Ultrasound Lecture 2 Beamwidth TT Liu, BE280A, UCSD, Fall 2007 TT Liu, BE280A, UCSD, Fall 2007 \"z D Source:wikipedia ! In general Plane Wave Approxi...
UCSD >> CO >> 2 (Fall, 2008)
Atmospheric carbon dioxide, Mauna Loa, Hawaii, 1958-2006 \"The Keeling Curve\" Updated: January 9, 200\\7 Data source: C. D. Keeling, S. C. Piper, R. B. Bacastow, M. Wahlen, T. P. Whorf, M. Heimann, and H. A. Meijer, Exchanges of atmospheric CO2 and 13...
UCSD >> BE >> 280 (Fall, 2008)
BENG280A, Principles of Biomedical Imaging Fall Quarter 2008 INFORMATION SHEET Instructor: 09/17/08 HO #1 Thomas Liu, Department of Radiology Center for Functional Magnetic Resonance Imaging (fMRI), Room 1001 (858) 822-0542 , ttliu@ucsd.edu Anna Le...
UCSD >> BE >> 280 (Fall, 2008)
Bioengineering 280A: Principles of Biomedical Imaging Fall Quarter 2008 Tentative Syllabus Week 1 Thursday 9/25 Week 2 Tuesday 9/30 Thursday 10/02 Week 3 Tuesday 10/07 Thursday 10/09 Week 4 Tuesday 10/14 Thursday 10/16 Week 5 Tuesday 10/21 Thursday 1...
UCSD >> BE >> 280 (Fall, 2008)
BENG280A, Principles of Biomedical Imaging Fall Quarter 2008 10/1/08 HOMEWORK #1 Due at the start of Class on Thursday 10/9/08 Homework policy: Late homeworks will be marked down by 20% per day. If you know that you need to turn in a homework late ...
UCSD >> BE >> 280 (Fall, 2008)
BENG280A, Principles of Biomedical Imaging Fall Quarter 2008 10/9/08 HOMEWORK #2 Due at the start of Class on Thursday 10/16/08 Homework policy: Late homeworks will be marked down by 20% per day. If you know that you need to turn in a homework late...
UCSD >> BE >> 200 (Fall, 2008)
Neuroscience 200C Spring Quarter Lecturer: Tom Liu Magnetic Resonance Imaging Pre-lecture Notes April 9, 2008 In these notes we will review some basic concepts that will help you follow next Tuesdays lecture on the basics of magnetic resonance imag...
UCSD >> BE >> 280 (Fall, 2008)
Neuroscience 200C Spring Quarter Lecturer: Tom Liu Magnetic Resonance Imaging Pre-lecture Notes April 9, 2008 In these notes we will review some basic concepts that will help you follow next Tuesdays lecture on the basics of magnetic resonance imag...
UCSD >> BE >> 280 (Fall, 2008)
BENG280A, Principles of Biomedical Imaging Fall Quarter 2008 10/14/08 HOMEWORK #3 Due at the start of Class on Thursday 10/23/08 Readings: Sections 2.2.3; 2.2.5, 2.2.6; 2.4, 2.5, 2.6, 3.2; 3.3; 6.3 Preview Section 2.8 Problems: 1. Prove the followi...
UCSD >> BE >> 280 (Fall, 2008)
BENG280A, Principles of Biomedical Imaging Fall Quarter 2008 HOMEWORK #4 Due at the start of Class on Thursday 10/30/08 Readings: Section 2.8 and review Chapter 6 as necessary. Problems: 10/21/08 1. Generalized functions. Recall that delta function...
UCSD >> BE >> 280 (Fall, 2008)
BE280A, Principles of Biomedical Imaging Fall Quarter 2008 BE280A Midterm Project Assignment 10/29/08 Due Date: Completed project (hard copy) is due at 12 pm (noon) on Monday, November 10, 2008 please turn in at Room 1001 of the fMRI Center betwee...
UCSD >> BE >> 280 (Fall, 2008)
4. (10 points) G (k) =| k | w(k) (a) (3 points) Ram-Lak Filter: \"k% w(k) = rect $ \' # 2k max k% G (k) =| k | rect $ \' # 2k max \" k % \" k % = k max $ rect $ \' ( )$ \' $ \' # 2k max # g(l) = 2(k max ) 2 sinc(2k max l) ( (k max ) 2 s...
UCSD >> BE >> 280 (Fall, 2008)
BENG280A, Principles of Biomedical Imaging Fall Quarter 2008 HOMEWORK #5 Due in Class on Thursday 11/13/08 Readings: View the MRI safety video on the website. Read Nishimura chapters 1 through 5 (Focus on chapters 3-5). Problems: (In Nishimura unless...
UCSD >> BE >> 280 (Fall, 2008)
BENG280A, Principles of Biomedical Imaging Fall Quarter 2008 HOMEWORK #6 Due in Class on Thursday 11/20/08 Readings: Read Chapters 6 and 7 in Nishimura Problems: (In Nishimura unless otherwise stated) 11/13/08 1. Problem 5.1 2. Problem 5.6 3. Probl...
UCSD >> BE >> 280 (Fall, 2008)
BENG280A, Principles of Biomedical Imaging Fall Quarter 2008 HOMEWORK #7 Due in Class on Thursday 12/04/08 Readings: Review Chapters 6 and 7 in Nishimura Read Chapters 10 and 11 in Prince and Links Problems: 11/18/08 1. Consider the slice profile s...
UCSD >> BE >> 280 (Fall, 2008)
BE280A, Principles of Biomedical Imaging Fall Quarter 2008 BE280A Final Project Assignment 11/18/08 Due Date: As agreed upon in class, the completed project (hard copy) will be due in my office on Tuesday, December 9, 2008 by 5 pm. In addition to t...
UCSD >> BE >> 280 (Fall, 2008)
Goals of the Course Bioengineering 280A Principles of Biomedical Imaging Fall Quarter 2008 Lecture 1 1. Develop a rm understanding of the fundamentals of medical imaging, including an appreciation for the common principles underlying the various mod...
UCSD >> BE >> 280 (Fall, 2008)
Bioengineering 280A Principles of Biomedical Imaging Fall Quarter 2008 X-Rays Lecture 1 TT Liu, BE280A, UCSD Fall 2008 TT Liu, BE280A, UCSD Fall 2008 EM spectrum X-Ray Tube Usually tungsten is used for anode Molybdenum for mammography Tungsten l...
UCSD >> BE >> 280 (Fall, 2008)
Topics Review of Signal Expansions Linearity Superposition Convolution Bioengineering 280A Principles of Biomedical Imaging Fall Quarter 2008 X-Rays Lecture 2 TT Liu, BE280A, UCSD Fall 2008 TT Liu, BE280A, UCSD Fall 2008 Kronecker Delta Funct...
UCSD >> BE >> 280 (Fall, 2008)
Computed Tomography Bioengineering 280A Principles of Biomedical Imaging Fall Quarter 2008 CT Lecture 1 TT Liu, BE280A, UCSD Fall 2008 TT Liu, BE280A, UCSD Fall 2008 Suetens 2002 Computed Tomography Fan Beam Scanner Generations Parallel Beam ...
UCSD >> BE >> 280 (Fall, 2008)
Topics Projection Slice Theorem Fourier Transforms Bioengineering 280A Principles of Biomedical Imaging Fall Quarter 2008 CT/Fourier Lecture 2 TT Liu, BE280A, UCSD Fall 2007 TT Liu, BE280A, UCSD Fall 2007 Projection Slice Theorem G(\",#) = Sign...
UCSD >> BE >> 280 (Fall, 2008)
Topics Modulation Modulation Transfer Function Convolution/Multiplication Revisit Projection-Slice Theorem Filtered Backprojection Bioengineering 280A Principles of Biomedical Imaging Fall Quarter 2008 CT/Fourier Lecture 3 TT Liu, BE280A, UCSD...
UCSD >> BE >> 280 (Fall, 2008)
Topics Sampling Requirements in CT Sampling Theory Aliasing Bioengineering 280A Principles of Biomedical Imaging Fall Quarter 2007 CT/Fourier Lecture 4 TT Liu, BE280A, UCSD Fall 2007 TT Liu, BE280A, UCSD Fall 2007 CT Sampling Requirements What...
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Topics The concept of spin Precession of magnetic spin Relaxation Bioengineering 280A Principles of Biomedical Imaging Fall Quarter 2008 MRI Lecture 1 TT. Liu, BE280A, UCSD Fall 2008 TT. Liu, BE280A, UCSD Fall 2008 Spin Intrinsic angular mome...
UCSD >> BE >> 280 (Fall, 2008)
Bloch Equation M i + M y j ( M z $ M 0 )k dM = M \" #B $ x $ dt T2 T1 Precession Transverse Relaxation Longitudinal Relaxation Bioengineering 280A Principles of Biomedical Imaging Fall Quarter 2008 MRI Lecture 2 ! i, j, k are unit vectors in the x,y...
UCSD >> BE >> 280 (Fall, 2008)
Sampling in k-space Bioengineering 280A Principles of Biomedical Imaging Fall Quarter 2008 MRI Lecture 3 Thomas Liu, BE280A, UCSD, Fall 2008 Thomas Liu, BE280A, UCSD, Fall 2008 Aliasing Aliasing Thomas Liu, BE280A, UCSD, Fall 2008 Thomas Liu, ...
UCSD >> BE >> 280 (Fall, 2008)
Static Inhomogeneities In the ideal situation, the static magnetic eld is totally uniform and the reconstructed object is determined solely by the applied gradient elds. In reality, the magnet is not perfect and will not be totally uniform. Part of t...
UCSD >> BE >> 280 (Fall, 2008)
RF Excitation Bioengineering 280A Principles of Biomedical Imaging Fall Quarter 2008 MRI Lecture 5 Thomas Liu, BE280A, UCSD, Fall 2008 Thomas Liu, BE280A, UCSD, Fall 2008 From Levitt, Spin Dynamics, 2001 RF Excitation At equilibrium, net magnet...
UCSD >> BE >> 280 (Fall, 2008)
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UCSD >> BE >> 280 (Fall, 2008)
Moving Spins So far we have assumed that the spins are not moving (aside from thermal motion giving rise to relaxation), and contrast has been based upon T1, T2, and proton density. We were able to achieve different contrasts by adjusting the appropr...
UCSD >> BE >> 280 (Fall, 2008)
Bioengineering 280A Principles of Biomedical Imaging Fall Quarter 2008 Ultrasound Lecture 1 Sonosite 180 From Suetens 2002 Acuson Sequoia TT Liu, BE280A, UCSD, Fall 2008 TT Liu, BE280A, UCSD, Fall 2008 Basic System Basic System Echo occurs at...
UCSD >> BE >> 280 (Fall, 2008)
Single-slit Diffraction Bioengineering 280A Principles of Biomedical Imaging Fall Quarter 2008 Ultrasound Lecture 2 Beamwidth TT Liu, BE280A, UCSD, Fall 2008 TT Liu, BE280A, UCSD, Fall 2008 \"z D Source:wikipedia ! In general Plane Wave Approxi...
UCSD >> CSE >> 237 (Fall, 2008)
Architectural Modeling of Compressed Instruction Set in Retargetable Compiler-Simulator Framework AUTHOR INFO REMOVED Software For Embedded Systems Dept. of Information and Computer Science University of California, Irvine, CA 92697, USA March 2000 ...
UCSD >> CSE >> 237 (Fall, 2008)
Introduction: The advancement in technology and proliferation of intelligent devices has seen the rapid transformation of human lives. Embedded devices, with their pervasive reach, are being used more and more in unthinkable domains and applications....
UCSD >> CSE >> 237 (Fall, 2008)
HDL / C Interface Exploration by A report submitted in partial fulfillment of the requirements of ICS212 2002 Introduction to Embedded Systems Department of ICS University Of California, Irvine -0- Contents 0. Acknowledgements 1. Goal 2. Backgr...
UCSD >> CSE >> 237 (Fall, 2008)
Image Compression Application on Battery-aware Embedded Systems Dept. of Electrical & Computer Engineering University of California at Irvine 1 Introduction Image compression is widely used in space [4], industrial monitoring, wireless communicati...
UCSD >> CSE >> 237 (Fall, 2008)
Code Compression in Embedded Systems by ID Date: March 22, 2002 Code Compression in Embedded Systems _ Introduction Embedded systems are becoming increasingly popular as more and more consumers accept the carrying electronic devices with them. For ...
UCSD >> CSE >> 237 (Fall, 2008)
Hardware Impl ementations of Cryptographi c Systems Survey Report for ICS212 Instructor: Prof. Rajesh K. Gupta Submitted by: Date: March21st, 2002 1 Index .1. Introduction ..3 2. Cryptography Processors5 2.1 Goodman & Chandrakasan Implementation ...
UCSD >> CSE >> 237 (Fall, 2008)
GXMI: Proposing a General Extensible Model for Using PDAs to Interact With Embedded Systems Ph.D. Student, UCI model. In Section 3 GXMI will be introduced and the format of messages will be defined. In Section 4 we talk about implemented components a...
UCSD >> CSE >> 237 (Fall, 2008)
Power Usage in Memory File Systems ICS 212 Abstract The need for persistent storage in embedded devices has led to the need for efficient file systems. Such file systems need to be profiled for power usage so that power-aware embedded systems will b...
UCSD >> CSE >> 237 (Fall, 2008)
MICRO-CONTROLLED READING OF IBUTTON USING ALTERA FPGA BOARD by of ICS 212 Introduction to Embedded Systems 2002 UC, Irvine i TABLE OF CONTENTS Acknowledgments .ii Introduction.iii Chapter I: Memory iButtons An Overview .2 Chapter II: iButton to...
UCSD >> CSE >> 237 (Fall, 2008)
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UCSD >> CSE >> 237 (Fall, 2008)
CSE 237B Project Report Implementing KLT Algorithm on IPAQ Author : Ajit Chourasia 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 1 Implementing KLT Algorithm on iPAQ 1 Implementing KLT Algorithm on iPAQ .. 1 1.1 Problem Statement. 2 1.2...
UCSD >> CSE >> 237 (Fall, 2008)
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UCSD >> CSE >> 237 (Fall, 2008)
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UCSD >> CSE >> 237 (Fall, 2008)
Geographical Short Messaging and Multicasting Project Report (ICS 212) Winter 2002 Abstract: This report describes the implementation of short messaging and multicasting amongst ubiquitous hand held devices. The implementation is based on client ser...
UCSD >> CSE >> 237 (Fall, 2008)
A Project Report on Multicasting in eCos Submitted as part of the requirements of course ICS 212 Introduction to Embedded Systems Submitted to: Dr. Rajesh Gupta Submitted by: Maulik Oza (SID#32504699) Shireesh Verma (SID# 88284288) Department ...
UCSD >> CSE >> 237 (Fall, 2008)
Campus Navigator ICS 212 project, Winter 2002 by Introduction In the past few years we have witnessed an exciting race for miniaturization of computing devices. It is possible nowadays to build a computer equivalent in computational power with the p...
UCSD >> CSE >> 237 (Fall, 2008)
ICS 212 Intro of Embedded System Final Report Network booting for Embedded Linux Motivation: The idea comes from a little x86 based device, which can boot itself using some sort of on board flash/EEPROM and has build-in tftp/UDP/IP stack to support...
UCSD >> CSE >> 237 (Fall, 2008)
Palm-Integrated Sensors Using Altera FPGA Board ICS 213 Project Report March 2001 Project Web Site: http:/www.ics.uci.edu/~isse/proj213/ Contents Introduction .. 3 Chapter 1. Description of the hardware used in the project . 5 Temperature Sensor....
UCSD >> CSE >> 237 (Fall, 2008)
XML based Hierarchical ADL: xHADL 1. INTRODUCTION ADL is almost a general concept that has been used in different areas. In this project I focused on EXPRESSION ADL [1] and xHADL is the proposed solution to problems of this ADL. In fact EXPRESSION AD...
UCSD >> WWW-CSE >> 253 (Fall, 2008)
) 6 3 ( 1 # % 9 6 # 1 5 6 6 6 % # % 9 \" ( 1 5 ( ( % # % # % 6 # 1 5 1 \' 6 1 1 y | z { y } y y y { ) 6 6 ( % 1 ( ( 1 5 % 1 5 # 3 % % 6 3 #...
UCSD >> CSE >> 237 (Fall, 2008)
...
UCSD >> CSE >> 237 (Fall, 2008)
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UCSD >> CSE >> 237 (Fall, 2008)
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A QUICK INTRO TO PRACTICAL OPTIMIZATION TECHNIQUES 0. NO SILVER BULLETS HERE. 1. Set Compiler Options Appropriately: Select processor architecture: Enables compiler to make full use of instructions which are supported by the processor Compiler perfor...
UCSD >> CSE >> 237 (Fall, 2008)
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UCSD >> GS >> 09 (Fall, 2008)
Participant\'s Name: _ Please Print UNIVERSITY OF CALIFORNIA, San Diego MMW4 and Christianity in Paris Global Seminar and its\' activities during SS2 Waiver of Liability, Assumption of Risk, and Indemnity Agreement Waiver: In consideration of being p...
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