pg-4035, virtual microscopy in the cloud, by wojciech tarnawski
DESCRIPTION
Presentation PG-4035, Virtual Microscopy in the cloud, by Wojciech Tarnawski at the AMD Developer Summit (APU13) Nov. 11-13, 2013.TRANSCRIPT
1 | PRESENTATION TITLE | NOVEMBER 21, 2013 | CONFIDENTIAL
VIRTUAL MICROSCOPY IN THE CLOUD WOJCIECH TARNAWSKI , CSO
MICROSCOPEIT LTD.
2 | PRESENTATION TITLE | NOVEMBER 21, 2013 | CONFIDENTIAL
Virtual Microscopy in the Cloud Wojciech Tarnawski, PhD, CSO MicroscopeIT Ltd., Wroclaw, Poland
3 | PRESENTATION TITLE | NOVEMBER 21, 2013 | CONFIDENTIAL
MICROSCOPY IS COMPLICATED
! Different formats, different producers.
! Different software for different image processing tasks.
! Image analysis takes time.
! Open Source vs. Commercial Software.
! Image types: 2D (fluorescence, phase-contrast), 3D (confocal), 4D (3D objects in time), different channels targeting different molecular elements.
CreaMve Commons 2.0, Nicole Yeary's photos via GeRy Images
4 | PRESENTATION TITLE | NOVEMBER 21, 2013 | CONFIDENTIAL
WHAT IS VIRTUM?
Cloud Computing Image processing pipeline integrated accessed in the web browser.
Flexibility All formats, dimensions and modality supported
Acceleration Time consuming image analysis ported to GPU.
Information Retrieval Phenotype detection of biologically relevant information directly from images.
Robust and fast workflow-based image analysis Save time thanks to intelligent algorithms with „visual” development.
Image credit: leverhawk.com, Why is cloud integraMon sMll an adopMon barrier, 2012.
5 | PRESENTATION TITLE | NOVEMBER 21, 2013 | CONFIDENTIAL
IN ACTION
Our system: 32 GPU cards (6 donated by AMD)
Database
Data acquisi:on
" Work-‐flow based image processing and task scheduling
6 | PRESENTATION TITLE | NOVEMBER 21, 2013 | CONFIDENTIAL
FEATURES, APPLICATIONS Visualization (Virtual Microscopy)
Data Analysis
E-learning
Teleconferencing teleconsultations
High-Content and High-Throughput
Screening
Quantitative data analysis
Scientific research
Clinical trials
Biotechnology
Medicine and biology
7 | PRESENTATION TITLE | NOVEMBER 21, 2013 | CONFIDENTIAL
Visualiza:on 2D Image Series WSI VisualizaMon 3D Image Series Movie ProjecMon 3D Geometry Viewer Rendering ReconstrucMon
Input Data Types
Not Ordered WSI Image z-‐stacks Time-‐Lapse Time-‐Lapse Images ( Image Pyramids) Image Series Z-‐Stacks
8 | PRESENTATION TITLE | NOVEMBER 21, 2013 | CONFIDENTIAL
INPUT DATA TYPES : NOT-‐ORDERED SETS AND TIME-‐LAPSE IMAGE SERIES
9 | PRESENTATION TITLE | NOVEMBER 21, 2013 | CONFIDENTIAL
INPUT DATA TYPES : Z-‐STACKS AND TIME-‐LAPSE Z-‐STACKS
10 | PRESENTATION TITLE | NOVEMBER 21, 2013 | CONFIDENTIAL
INPUT DATA TYPES : IMAGE PYRAMID
11 | PRESENTATION TITLE | NOVEMBER 21, 2013 | CONFIDENTIAL
Visualiza:on 2D Image Series WSI VisualizaMon 3D Image Series Movie ProjecMon 3D Geometry Viewer Rendering ReconstrucMon
Data Analysis 2D Image Processing 2-‐3D Image ReconstrucDon Time-‐Dependent Analysis Post-‐Processing and Analysis
Image Processing and Analysis Library
2-‐3D Mesurements Image Preprocessing 2-‐3D Object SegmentaDon 2-‐3D Object Analysis StaDsDcs
Input Data Types
Not Ordered WSI Image z-‐stacks Time-‐Lapse Time-‐Lapse Images ( Image Pyramids) Image Series Z-‐Stacks
12 | PRESENTATION TITLE | NOVEMBER 21, 2013 | CONFIDENTIAL
CLOUD COMPONENTS (BACK-‐END) 1/3 Image Processing and Analysis Library : about 70 methods tailored for microscopy imaga data implemented on CPU and GPU
2-‐3D Mesurements
Image Preprocessing : noise removal, contrast improvement, inhomogeneous lighDng removal, opDcal deconvoluDon, 2-‐3D Image SDtching, Histogram-‐based processing, MulD-‐channel Image Composing, Image ArithmeDc, Edge DetecDon, … etc.
2-‐3D Object SegmentaDon : automaDc or machine-‐learning methods for segmentaDon of 2-‐3D objects e.g. 2-‐3D Cell Tracking Advanced SegmentaDon in mulD-‐dimensional space composed with texture and color features, AcDve Contour and AcDve Mesh, Threshold -‐ and Morphology – based SegmentaDon, Mean-‐Shi[, …
2-‐3D Object Analysis : Split into 2-‐3D Ellipsoids e.g. for highly clustered cells , Morphology Operatos , Weighted Distance Transform, Voronoi TriangulaDon, Object RecogniDon module for Cell Phase ClassificaDon by Markov chains
StaDsDcs Module – PCA, Basic StaDsDcs, Cluster Analysis,
13 | PRESENTATION TITLE | NOVEMBER 21, 2013 | CONFIDENTIAL
3D IMAGE SEGMENTATION : ACTIVE MESH
14 | PRESENTATION TITLE | NOVEMBER 21, 2013 | CONFIDENTIAL
CLOUD COMPONENTS (BACK-‐END) 1/3 Image Processing and Analysis Library : about 70 methods tailored for microscopy imaga data implemented on CPU and GPU
* A Robust Algorithm for Segmen:ng and Tracking Clustered Cells in Time-‐Lapse Fluorescent Microscopy Tarnawski, W. ; Kurtcuoglu, V. ; Lorek, P. ; Bodych, M. ;RoRer, J. ; Muszkieta, M. ; Piwowar, L. ; Poulikakos, D. ;Majkowski, M. ; Ferrari, A. Biomedical and Health InformaMcs, IEEE Journal of Volume: 17 , Issue: 4 PublicaMon Year: 2013 , Page(s): 862 -‐ 869
Workflow-‐based image processing
15 | PRESENTATION TITLE | NOVEMBER 21, 2013 | CONFIDENTIAL
WORKFLOW – BASED IMAGE PROCESSING AND ANALYSIS
16 | PRESENTATION TITLE | NOVEMBER 21, 2013 | CONFIDENTIAL
USE CASES
! Detection of nuclei and cytoplasm in 80 000 images (512x512 pixels) takes about 2 hours on multi-core CPU (AMD Athlon(tm) II X4 640 Processor). GPU provided up to 4x acceleration
! Optical deconvolution : about 25x acceleration for 512x512 image
! 3D-dimensional diffuse filter on image-stack (z-stack with 1920x1080) : about 10x acceleration
17 | PRESENTATION TITLE | NOVEMBER 21, 2013 | CONFIDENTIAL
CLOUD COMPONENTS (BACK-‐END) 2/3
Image Processing and Analysis Library : about 70 methods tailored for microscopy imaga data implemented on CPU and GPU
Task Scheduler to provide image analysis results for many users.
Scheduling approach :
Scheduler –> Executor –> Worker –> Task
-‐ Schedules image processing tasks on the CPU & GPU cluster. -‐ Monitors CPU, GPU, memory, storage usage. -‐ OpMmizes scalability.
18 | PRESENTATION TITLE | NOVEMBER 21, 2013 | CONFIDENTIAL
Image Processing and Analysis Library : about 70 methods tailored for microscopy imaga data implemented on CPU and GPU
Task Scheduler to provide image analysis results for many users.
Database Module -‐ to store the microscopic image data
Database Module provides upload data module that supports:
• about 100 microscopic image data formats (i.e. lsm, nd2, oly, mulD-‐channel , 16-‐bit Dff, basic graphic formats, …)
• compressed images series (zip)
• filename parser to upload image series ordered by channel, z-‐stack layers, Dme-‐points, …
• users data are fully organized
• users can be assigned to many projects
CLOUD COMPONENTS (BACK-‐END) 3/3
19 | PRESENTATION TITLE | NOVEMBER 21, 2013 | CONFIDENTIAL
PROJECT DATA ORGANIZATION
20 | PRESENTATION TITLE | NOVEMBER 21, 2013 | CONFIDENTIAL
CLIENT (GUI) COMPONENTS
Graphical User Interface (GUI) installed as a plugin in the web browser:
! Designed for touch-‐based devices.
! Designed to tag microscopic image series with metadata.
! Includes different viewers to visualize mulM-‐dimensional images.
! Provides „visual” interface to design the workflow for image processing and analysis.
! Provides tools to select the image regions for futher iamge analysis.
21 | PRESENTATION TITLE | NOVEMBER 21, 2013 | CONFIDENTIAL
! MicroscopeIT Ltd. Kutnowska 1-‐2 Wroclaw, Poland
! Contact: [email protected] Tel. +48 605 111 445
Skype:tar_woj
22 | PRESENTATION TITLE | NOVEMBER 21, 2013 | CONFIDENTIAL
DISCLAIMER & ATTRIBUTION
The informaMon presented in this document is for informaMonal purposes only and may contain technical inaccuracies, omissions and typographical errors.
The informaMon contained herein is subject to change and may be rendered inaccurate for many reasons, including but not limited to product and roadmap changes, component and motherboard version changes, new model and/or product releases, product differences between differing manufacturers, sotware changes, BIOS flashes, firmware upgrades, or the like. AMD assumes no obligaMon to update or otherwise correct or revise this informaMon. However, AMD reserves the right to revise this informaMon and to make changes from Mme to Mme to the content hereof without obligaMon of AMD to noMfy any person of such revisions or changes.
AMD MAKES NO REPRESENTATIONS OR WARRANTIES WITH RESPECT TO THE CONTENTS HEREOF AND ASSUMES NO RESPONSIBILITY FOR ANY INACCURACIES, ERRORS OR OMISSIONS THAT MAY APPEAR IN THIS INFORMATION.
AMD SPECIFICALLY DISCLAIMS ANY IMPLIED WARRANTIES OF MERCHANTABILITY OR FITNESS FOR ANY PARTICULAR PURPOSE. IN NO EVENT WILL AMD BE LIABLE TO ANY PERSON FOR ANY DIRECT, INDIRECT, SPECIAL OR OTHER CONSEQUENTIAL DAMAGES ARISING FROM THE USE OF ANY INFORMATION CONTAINED HEREIN, EVEN IF AMD IS EXPRESSLY ADVISED OF THE POSSIBILITY OF SUCH DAMAGES.
ATTRIBUTION
© 2013 Advanced Micro Devices, Inc. All rights reserved. AMD, the AMD Arrow logo and combinaMons thereof are trademarks of Advanced Micro Devices, Inc. in the United States and/or other jurisdicMons. SPEC is a registered trademark of the Standard Performance EvaluaMon CorporaMon (SPEC). Other names are for informaMonal purposes only and may be trademarks of their respecMve owners.