Fluorescence Microscopy and Bioimage Processing Flashcards
1
Q
What is the relationship between image distance, object distance and image size?
A
- smaller the image distance, larger the object distance, smaller the image size
- larger the image distance, smaller the object distance, larger the image size
2
Q
Lens Maker formula
A
- 1/u - 1/v = 1/f
- u is object distance, v is image distance, f is focal point
- reveals focal length
3
Q
Total Magnification
A
- eyepiece x objective = total magnification
- e.g. eyepiece (10x) x objective (20x) = magnification 200x
4
Q
Eyepiece (microscope components)
A
- ocular, tube
- Essentially a projection lens (5x to 15x magnification)
- Adjustment of inter-pupillary distance on eyepieces for personal focusing is critical
5
Q
“Inverted” microscopy
A
- objective is below the sample
6
Q
“Upright” microscopy
A
- objective is above the sample
7
Q
Condenser
A
- focus the light onto the specimen
- Aligns the light rays into a straight path
- Adjust for objective
8
Q
Refraction
A
- bending of light
- occurs as light passes from one medium into another medium with a different refractive index
9
Q
Refractive index
A
- a dimensionless number that gives the indication of the light bending ability of that medium
10
Q
Numerical aperture
A
- a measure of its ability to gather light and resolve fine specimen detail at a fixed object distance
11
Q
Equation for numerical aperture
A
- n x (sin u)
- u = angle of one-half the angular aperture (A)
- n = Refractive Index of imaging medium
- higher the total numerical aperture, the better the resolution
12
Q
Resolution
A
- the smallest distance between two points on a specimen that can still be distinguished as two separate entities
13
Q
Equation for resolution
A
- R = λ/(2 x NA)
- where λ is the wavelength and NA is the numerical aperture
14
Q
What is fluorescence?
A
- property of some atoms/molecules to absorb light (the excitation: Ex) of
short wavelength and emitting (Em) light of longer wavelength. - distance between the excitation and emission peaks is known as the Stokes shift
15
Q
Antibodies as a fluorescence labelling strategy
A
- Direct: Primary antibody is directly conjugated to a fluorophore
- Indirect: Primary antibody is indirectly detected by a labelled secondary antibody
16
Q
Gene transfer as a fluorescence labelling strategy
A
- bring in sequences/constructs into cell lines to make them shine green
- binding a small-molecule fluorophore
17
Q
What is a fluorescence microscope?
A
- uses different spectra from normal light microscopy
- uses different excitation wavelengths
- excitation filter only lets specific waves pass through, which excites the fluorophore and thus emits light
- light emission is captured by camera (specific for either red, green or blue)
18
Q
Advantages of using a fluorescence microscope
A
- better resolution
- allows to collect images in more than one colour
- cheaper and quicker to produce image than confocal microscopy
19
Q
What is confocal microscopy?
A
- scans sample with focused beam of light which eliminates/reduces background information
- use laser excitation source to force fluorophore to emit light, all light is emitted
- uses pinhole aperture to eliminate out of focus light, only a specific focal plane records it, provides crisp image
20
Q
What is a multiphoton microscope?
A
- goes to specific area of sample and excites specific fluorophores
- often used in neuroscience
- only produces fluorescence at the focal plane and produces no background fluorescence, a pinhole is not required
21
Q
Images and Pixels
A
- Digital images are composed of picture elements: pixels
- Each pixel has a numeric value (often related to detected light)
- 8-bit – unsigned integer: 28 = 256 different pixel values
- 16-bit – unsigned integer: 216 = 65536 different pixel values
- Digital images are a matrix of numbers -information
- Images that look the same can contain different pixel values
22
Q
RGB images
A
- In general, each color is represented using three 8-bit unsigned
integers: one for Red, one for Green, one for Blue - usually not very good for quantitative analysis
- Multichannel / composite images are better for analysis, but
need to be converted to RGB for display
23
Q
Pixel depth
A
- number of bits used to represent each pixel in RGB space (e.g. 8-bit RGB)
- Each integer value defines how much of each primary colour should be mixed together to create the final colour
- 256 x 256 x 256 = 16,777,216 different colours (more than our
eye can distinguish!)
24
Q
Filters in image analysis
A
- Successfully extracting useful information from microscopy images usually requires 1) image acquisition, 2) image processing and 3) image analysis
- Images are frequently pre-processed with filters to improve the
effectiveness of image analysis (i.e. clean up of image, improve SNR)
25
Q
Deconvolution
A
- corrects the systematic error of blur (loss of contrast in smaller features) and reconstructs true image
26
Q
Gaussian blur
A
- image is convoluted with a Gaussian function for smoothing to reduce the image noise
27
Q
Subtract background
A
- Removes backgrounds from images
- A local background value is determined for every pixel by averaging over a very large area
28
Q
Thresholding
A
- a technique for dividing an image into “foreground” and “background” pixels.
- Global threshold: setting cut-off pixel value and divide all pixels below (background) and over (foreground) this value (entire image)
29
Q
Segmentation
A
- the process of partitioning a digital image into multiple segments
- helps to reduce complexity of image and make subsequent processing or analysis of the image easier
- the process of labelling each pixel in an image so that pixels with the same label have similar visual characteristics
- Preprocess the image, Apply threshold, Create/Manipulate mask (binarization)
- commonly used to find objects and boundaries and quantify their numbers, size, intensity, density, etc
