Fluorescence Microscopy and Bioimage Processing

Question 1

What is the relationship between image distance, object distance and image size?

Answer 1

• smaller the image distance, larger the object distance, smaller the image size
• larger the image distance, smaller the object distance, larger the image size

Question 2

Lens Maker formula

Answer 2

• 1/u - 1/v = 1/f
• u is object distance, v is image distance, f is focal point
• reveals focal length

Question 3

Total Magnification

Answer 3

• eyepiece x objective = total magnification
• e.g. eyepiece (10x) x objective (20x) = magnification 200x

Question 4

Eyepiece (microscope components)

Answer 4

• ocular, tube
• Essentially a projection lens (5x to 15x magnification)
• Adjustment of inter-pupillary distance on eyepieces for personal focusing is critical

Question 5

“Inverted” microscopy

Answer 5

• objective is below the sample

Question 6

“Upright” microscopy

Answer 6

• objective is above the sample

Question 7

Condenser

Answer 7

• focus the light onto the specimen
• Aligns the light rays into a straight path
• Adjust for objective

Question 8

Refraction

Answer 8

• bending of light
• occurs as light passes from one medium into another medium with a different refractive index

Question 9

Refractive index

Answer 9

• a dimensionless number that gives the indication of the light bending ability of that medium

Question 10

Numerical aperture

Answer 10

• a measure of its ability to gather light and resolve fine specimen detail at a fixed object distance

Question 11

Equation for numerical aperture

Answer 11

• 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

Question 12

Resolution

Answer 12

• the smallest distance between two points on a specimen that can still be distinguished as two separate entities

Question 13

Equation for resolution

Answer 13

• R = λ/(2 x NA)
• where λ is the wavelength and NA is the numerical aperture

Question 14

What is fluorescence?

Answer 14

• 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

Question 15

Antibodies as a fluorescence labelling strategy

Answer 15

• Direct: Primary antibody is directly conjugated to a fluorophore
• Indirect: Primary antibody is indirectly detected by a labelled secondary antibody

Question 16

Gene transfer as a fluorescence labelling strategy

Answer 16

• bring in sequences/constructs into cell lines to make them shine green
• binding a small-molecule fluorophore

Question 17

What is a fluorescence microscope?

Answer 17

• 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)

Question 18

Advantages of using a fluorescence microscope

Answer 18

• better resolution
• allows to collect images in more than one colour
• cheaper and quicker to produce image than confocal microscopy

Question 19

What is confocal microscopy?

Answer 19

• 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

Question 20

What is a multiphoton microscope?

Answer 20

• 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

Question 21

Images and Pixels

Answer 21

• 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

Question 22

RGB images

Answer 22

• 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

Question 23

Pixel depth

Answer 23

• 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!)

Question 24

Filters in image analysis

Answer 24

• 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)

Question 25

Deconvolution

Answer 25

• corrects the systematic error of blur (loss of contrast in smaller features) and reconstructs true image

Question 26

Gaussian blur

Answer 26

• image is convoluted with a Gaussian function for smoothing to reduce the image noise

Question 27

Subtract background

Answer 27

• Removes backgrounds from images
• A local background value is determined for every pixel by averaging over a very large area

Question 28

Thresholding

Answer 28

• 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)

Question 29

Segmentation

Answer 29

• 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