mercoledì 21 marzo 2012 Eliot Salant-
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1
2 Eliot Salant-
3 Eliot Salant- IBM Haifa Research
4 Eliot Salant- IBM Haifa Research
5 Eliot Salant- IBM Haifa Research Project Coordinator, VISION Cloud
6 Eliot Salant- IBM Haifa Research Project Coordinator, VISION Cloud
7 Eliot Salant- IBM Haifa Research Project Coordinator, VISION Cloud Project Coordinator, ENSURE
8 VISION Cloud A storage cloud for ehealth Eliot Salant- salant@il.ibm.com IBM Haifa Research Project Coordinator, VISION Cloud Project Coordinator, ENSURE
9
10 Three year project
11 Three year project Budget of 5.5 Meuro
12 Three year project Budget of 5.5 Meuro 4 partners led by IBM
13 Three year project Budget of 5.5 Meuro 4 partners led by IBM Use cases from healthcare, media, telcos and enterprise
14 What is VISION Cloud? Three year project Budget of 5.5 Meuro 4 partners led by IBM Use cases from healthcare, media, telcos and enterprise
15
16 Commercial storage clouds exist
17 Commercial storage clouds exist
18 Commercial storage clouds exist So what s the problem?
19
20 Concerns for ehealth on the Cloud No defined borders
21 Concerns for ehealth on the Cloud No defined borders Economics
22 Concerns for ehealth on the Cloud No defined borders Economics Privacy Security
23 Concerns for ehealth on the Cloud No defined borders Economics Privacy Security Searchability
24
25 Run computations near storage Ex. Anonymization, image compression
26 Run computations near storage Ex. Anonymization, image compression Allow for rich, modifiable user metadata And keep metadata with the data object
27 Run computations near storage Ex. Anonymization, image compression Allow for rich, modifiable user metadata And keep metadata with the data object Search on key-value
28 Next generation of storage clouds Run computations near storage Ex. Anonymization, image compression Allow for rich, modifiable user metadata And keep metadata with the data object Search on key-value Semantic relationships between data objects
29
30 Healthcare Demonstration
31 Healthcare Demonstration DICOM Files Doctor
32 Healthcare Demonstration DICOM Files Doctor Upload Key Patient Study Bodypart Value "Müller" "ID" "Knee" Patient..n Study..n Series 0..n Image
33 Healthcare Demonstration DICOM Files Doctor Upload Key Patient Study Bodypart Patient..n Study..n Series 0..n Image Value "Müller" "ID" "Knee" Extract metadata and make them accessible 2
34 Healthcare Demonstration DICOM Files Doctor Upload Key Patient Study Bodypart Patient..n Study..n Series 0..n Image Value "Müller" "ID" "Knee" Extract metadata and make them accessible 2 Extract DICOM Images 3
35 Healthcare Demonstration Key Value Patient "Müller" Study "ID" Bodypart "Knee" Patient Study Series Image..n..n 0..n Upload Extract metadata and make them accessible 2 Extract DICOM Images 3 Doctor DICOM Files Study Series Transform into new related objects and create preview images 4 Key Value k v k2 v2 seriesid series_ Data Icon Key Value k v k2 v2 k3 v3 Data Preview- Image Key Value k v k2 v2 k3 v3 Data Preview- Image Key Value k v k2 v2 imageid image_ Data Preview- Image Key Value k v k2 v2 k3 v3 Key Value k v k2 v2 k3 v3 Key Value k v k2 v2 k3 v3 Image
36 Healthcare Demonstration Key Value Patient "Müller" Study "ID" Bodypart "Knee" Patient Study Series Image..n..n 0..n Upload Extract metadata and make them accessible 2 Extract DICOM Images 3 5 Finally Doctor DICOM Files Study Series Transform into new related objects and create preview images 4 Key Value k v k2 v2 seriesid series_ Data Icon Key Value k v k2 v2 k3 v3 Data Preview- Image Key Value k v k2 v2 k3 v3 Data Preview- Image Key Value k v k2 v2 imageid image_ Data Preview- Image Key Value k v k2 v2 k3 v3 Key Value k v k2 v2 k3 v3 Key Value k v k2 v2 k3 v3 Image
37 Healthcare Demonstration Doctor Key Patient Study Bodypart Upload Patient..n Study..n Series 0..n Image Value "Müller" "ID" "Knee" Extract metadata and make them accessible 2 DICOM Files Transform into new related objects and create preview images 4 Image Series Key Value kkey vvalue k2 kkey v2 vvalue k3 k2 k v3 v2 v k3 k2 v3 v2 k3 v3 Which VISION Extract Cloud features are DICOM demoed? Images Storing binary objects Storing of 3metadata Building simple Relationships via metadata Key Value kkey vvalue k2 kkey v2 vvalue k3 k2 k v3 v2 v k3 k2 v3 v2 imageid image_ Preview- Data Image Preview- Data Image Preview- Data Image Study Key k k2 seriesid Data Icon Value v v2 series_ Finally 5
38
39 Healthcare Demonstration Accessing Objects with Tablet PC
40 Healthcare Demonstration Accessing Objects with Tablet PC Logon Doctor / Patient
41 Healthcare Demonstration Accessing Objects with Tablet PC Logon / Doctor Patient 2 Multi-select Patient Provider Device Date
42 Healthcare Demonstration Accessing Objects with Tablet PC Logon / Doctor Patient 2 Multi-select Patient Provider Device Date 3 Select from List of Studies
43 Healthcare Demonstration Accessing Objects with Tablet PC Logon / Doctor Patient 2 Multi-select Patient Provider Device Date 3 Select from List of Studies 4 Select from List of Series
44 Healthcare Demonstration Accessing Objects with Tablet PC Logon / Doctor Patient 2 Multi-select Patient Provider Device Date 3 Select from List of Studies 4 Select from List of Series 5 Browse Images
45 Healthcare Demonstration Accessing Objects with Tablet PC Logon / Doctor Patient 2 Multi-select Patient Provider Device Date 3 Select from List of Studies 4 Select from List of Series 5 Browse Images What is demoed now? Search Retrieval of metadata Retrieval of binary objects
46
47 How can organizations share data, while respecting privacy? Off-line anonymization of data On-line masking of data
48 IBM Haifa research in ehealth data privacy How can organizations share data, while respecting privacy? Off-line anonymization of data On-line masking of data How to keep data anonymous.. Multiple accesses Cross-correlations
49 IBM Haifa research in ehealth data privacy How can organizations share data, while respecting privacy? Off-line anonymization of data On-line masking of data How to keep data anonymous.. Multiple accesses Cross-correlations
50 IBM Haifa research in ehealth data privacy How can organizations share data, while respecting privacy? Off-line anonymization of data On-line masking of data How to keep data anonymous.. Multiple accesses Cross-correlations
51 IBM Haifa research in ehealth data privacy How can organizations share data, while respecting privacy? Off-line anonymization of data On-line masking of data How to keep data anonymous.. Multiple accesses Cross-correlations
52 IBM Haifa research in ehealth data privacy How can organizations share data, while respecting privacy? Off-line anonymization of data On-line masking of data How to keep data anonymous.. Multiple accesses Cross-correlations
53 IBM Haifa research in ehealth data privacy How can organizations share data, while respecting privacy? Off-line anonymization of data On-line masking of data How to keep data anonymous.. Multiple accesses Cross-correlations +
54 IBM Haifa research in ehealth data privacy How can organizations share data, while respecting privacy? Off-line anonymization of data On-line masking of data How to keep data anonymous.. Multiple accesses Cross-correlations + =
55 IBM Haifa research in ehealth data privacy How can organizations share data, while respecting privacy? Off-line anonymization of data On-line masking of data How to keep data anonymous.. Multiple accesses Cross-correlations + =?
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