PPT-Image Reconstruction and Processing for Alpha Emitters

Yong Du PhD Department of Radiology Johns Hopkins University Conflict of Interest Disclosure Under a licensing agreement between the Radiopharmaceutical Imaging and Dosimetry LLC and the Johns Hopkins University Yong Du is entitled to a share of royalty received by the University on sales of iterative reconstruction software used to obtain some results in this presentation . Image Arithmetic. Arithmetic Image Operations (blending). 2. Two source images can be added, multiplied, one subtracted from the other or one divided by the other to produce a single destination (other types are also discussed later) . Lecture 12 / Homework 4. Breadth-First Search. Given source vertex S:. Find min. #edges to reach every vertex from S. (Assume source is vertex 0). 0. 1. 1. 2. 2. 3. Sequential . pseudocode. :. let Q be a queue. A Brief Overview. With slides contributed by. W.H.Chuang. and Dr. . . Avinash. L. Varna. Ravi . Garg. Sampling Theorem. Sampling: record a . signal. in the form of . samples. Nyquist. Sampling Theorem: . Ganesh. . Dasika. , Kevin Fan. 1. , Scott . Mahlke. 1. Parakinetics, Inc.. University of Michigan. Advanced Computer Architecture Laboratory. The Advent of the GPGPU. Increasingly popular substrate for HPC. Pumice Depth Below . Water . as a Function of Time. Behnaz. Hosseini. Havre, MESH . and Pumice Experiments. P. umice deposits from 2012 . Kermadec. Islands submarine eruption north of New Zealand. Havre caldera samples collected by MESH team using remotely operated vehicle Jason. 1. Image. Rich info. from visual data. Examples of images around us. natural photographic images; . . artistic and engineering drawings. scientific images (satellite, medical, etc.). “Motion pictures” => video. Chapter 9, Digital Image Processing, Gonzalez & Woods. Topics. Basic Morphological concepts. Four Morphological principles. Binary Morphological operations. Dilation & erosion. Hit-or-miss transformation. Mohammadhossein . Behgam. Agenda. Need for parallelism. Challenges. Image processing algorithms. Data handling & Load Balancing. Communication cost & performance. What is the problem?. Image Processing applications can be very computationally demanding due to:. http://users.cecs.anu.edu.au/~. yili/CVinNutshell.htm. Outline. Paper discussion. Image Processing (overview). Diffusion Process. Image Processing (filtering). Filter Banks. Image Processing (filtering). Divya Spandana . Marneni. Agenda. What is Big Data. Big Data and image processing. Why to analyze big images. Complexity involved in processing. Hadoop Image processing framework. Image Retrieval in big data. 1 INTRODUCTIONImage processing is the frequently used technique in vast areas like medical image astronomical data analysisand so on The collection of images is increased to petabytes in last few measurements for decommissioning facilities P Fichet (1), C Mougel (1), I Desnoyers (2), P Sardini (3), H Word (4) (1) Den – Service d’Etudes Analytiques et de Réactivité des Surfaces (SEAR Recognition Vol.7, No. 2 (2014), pp. 3 89 - 3 9 8 http://dx.d oi.org/10.14257/ijsip.2014.7. 2 . 3 6 ISSN: 2005 - 4254 IJSIP Copyright ⓒ 201 4 SERSC Extraction of Optic Cup in Retinal Fundus image Dept. Computer Science & Engineering. Hongtao Lu. 11/16/2016. Digital Image Processing, 3. rd. ed.. Preliminaries. Erosion and Dilation. Opening and Closing. The Hit-or-Miss Transformation. Some Basic Morphological Algorithms.