Three elements that uniquely describe a voxel position in real units (E.g., mm, cm)
Answer
- Image Origin; must not always be (0,0,0); (0,0)
- Image dimension
- Voxel/Pixel spacing (voxel/pixel) size
Card 3
Question
Why is the description of a voxel/pixel in real units so important?
Answer
Because image data is used to locate structures, pathologies, plan treatment (e.g. brain tumor surgery or radiotherapy), measure volumes, growth (of a disease), etc.
Card 4
Question
Which color model is mostly used?
Answer
Medical Images mostly use gray scale --> one channel
Card 5
Question
Where is hypo intensity and hyper intensity on the grayscale?
Answer
- Hypo intensity --> black
- Hyper intensity --> white
Card 6
Question
How many levels can we have for 1 byte/ 2 bytes?
Answer
- 256 for 1 byte (i.e., 28-1)
- 65536 levels for 2bytes (216)
- 0 à black ; 255/ 65535 à white
Card 7
Question
What does the pixel depth mean?
Answer
The pixel depth, or bit depth, determines the range of values that a particular raster file can store, which is based on the formula 2^n where n is the pixel depth.
Card 8
Question
Why is pixel depth important for medical images?
Answer
Pixel depth is then important for correct reading and storing of pixel data, but also for computational and memory consumption efficiency
Card 9
Question
What is DICOM?
Answer
Digital Imaging and Communications in Medicine (DICOM). Standard for storing, handling, printing, transmitting information in medical data
Card 10
Question
Why is DICOM used?
Answer
Enables integration of scanners, servers, workstations, printers, and other hardware from multiple vendors into a picture archiving and communication system (PACS)
Card 11
Question
What DICOM combines?
Answer
- Combines image data with meta-data (patient data, acquisition parameters)
Card 12
Question
What is the PACS system?
Answer
At the core of DICOM resides the PACS system, which is the computational unit at hospitals and clinics where imaging information is stored, and used to handle patient information related to imaging scans.
Card 13
Question
What are the parameters saved in the DICOM File format?
Answer
- Hardware, imaging à Model, Software
- Treatment-related à contrast agent
- Patient data --> Name, age, date of birth
Card 14
Question
What can DICOM handle?
Answer
- Hardware includes vendor type, specific parameter values (e.g. energy values for a CT scan), etc. Treatment and patient data are crucial as well to follow-up patients and to inform treating doctors.
- The second component (bottom) deals with the network protocol. Searching, querying, scheduling, etc. are part of this protocol
Card 15
Question
DICOM Network Protocol
Answer
- Search studies
- Restore
- Control treatment
- Scheduling, reporting, sharing workload
Card 16
Question
Structure of DICOM file format
Answer
A DICOM file, with extension .dcm, describes a single slice. It includes a header and data sets. The header has a so-called anarchic zone, left to the user, and it’s followed by the four chars D, I, C and M. The data sets follow the displayed structure. TAGs are predefined and part of the standard. In the next slides we will focus on some specific tags.
Card 17
Question
What is the difference between study and series?
Answer
Study: patient A has a CT scan
Series: patient A has a CT scan + MRI + Xray --> set of studies
Card 18
Question
What is the orientation TAG describing? DICOM?
Answer
The orientation TAG is described via two cosines directions. Setting/reading the image orientation is crucial to have a good readout of pixel data in world coordinates.
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Card 19
Question
What would be the TAG value in this image? (Here a image would be needed)
Answer
- There is a 45 degrees rotation (and cos(45)=0.707)
-
The cosines are then 6 values, and the TAG values would llike this: (0.707,-0.707,0, 0.707,0.707,0) the negative -0.707 corresponds to the component of the (new) LR axis moving in the negative direction of the (old) RA axis.
Card 20
Question
Voxel based representation
Answer
- These representations are derived directly from images
- Assign a label to each structure in the image
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