FAFF20: Multispectral Imaging

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1 FAFF20: Multispectral Imaging From astronomy to microscopy Stefan Kröll, Johan Axelsson Atomic Physics, LTH

2 Multispectral = many spectral bands Each pixel contains a spectrum

3 Spectral bands from the electromagnetic spectrum

4 Aim The aim of the course is to provide theoretical and practical knowledge on the generation of and information extraction from multi-spectral images in different wavelength regions and on different spatial scales. Basic knowledge on image processing should be attained.

5 Learning outcomes Knowledge and understanding For a passing grade the student must understand how techniques, common to all fields can be used to extract physical and chemical information from images have a basic knowledge on how spectroscopy allows to characterize materials and phenomena have basic knowledge on image analysis and multi-variate methods

6 Learning outcomes Competences and skills For a passing grade the student must be able to assess which spectral region is useful for a particular task be able to assess which characteristics are useful for a definite characterization of an image pixel be able to work with image analysis tools have an increased competence for presenting in writing an accomplished project have an increased experience in working in groups of two or four persons towards a common goal have improved knowledge on how to extract relevant data from literature references (project).

7 Learning outcomes Judgement and approach For a passing grade the student must be able to judge the power of multispectral imaging techniques to extract physical and chemical information from images recorded in different wavelength bands.

8 Examination Written exam, graded 0-6 where the requirement for pass is the grade 3. Compulsory laboratory exercises Digital Imaging Fluorescence Imaging Microscopy computer exercise Optional home assignments where each assignment can award up to 0.15 credit on the final exam. There are four assignments.

9 Course schedule

10 Spectral bands from the electromagnetic spectrum

11 Interactions between electromagnetic radiation and sample Electromagnetic radiation transfers energy Sample is composed of atoms, molecules By examining the resulting electromagnetic radiation after it has intracted with the sample - conclusions can be drawn about the object under study

12 Interactions between energy levels Absorption E 2 E 1 Emission E 2 E 1 Stimulated emission E 2 E 1

13 Basic arrangement for Multispectral imaging Source Sample Analyzer Detector Sun Lamps Lasers LEDs Synchrotron X-ray tube Plants Forests Tissue Cells Flames Chemical compounds etc. etc. Filters Spectrometers Monochromators Photodiodes Photomultiplier tubes CCD cameras CMOS cameras Image intensifiers

14 Course schedule

15 Microscopic imaging Example: Zebra fish brain with Light Sheet Microscope

16 Microscopic imaging: computer exercise

17 Microscopic imaging: computer exercise

18 Course schedule

19 PIXE Particle Induced X-ray Emission or Proton Induced X-ray Emission X-ray production crosssection is high for protons with a few MeV (~3 MeV). By directing a proton beam towards a sample very sensitive elemental analysis can be performed.

20 PIXE Particle Induced X-ray Emission or Proton Induced X-ray Emission

21 PIXE Hair follicle from Tycho Brahe

22 Course schedule

23 Combustion diagnostics: Laser-induced fluorescence Energy S 2 S Absorption Vibrational relaxation Fluorescence S

24 Combustion diagnostics: Laser-induced fluorescence

25 Course schedule

26 Medical optical imaging: UV-VIS-IR

27 Medical imaging: Optical imaging absorption of light

28 Optical tomography of tissue chromophores E15 4E15 Hemoglobin SO2 Water Scatter size Scatter dens.

29 Medical imaging: Contrast based on fluorescence Energy S 2 S Absorption Vibrational relaxation Fluorescence S

30 Fluorescence guided cervical tumor resection

31 Course schedule

32 Active remote sensing

33 Active remote sensing

34 Course schedule

35 Supernova 1604 Multispectral (X-ray, optical and infrared) representation of the last supervova and the Milky Way in 1604

36 Coronal temperature diagnostics derived from multilayer observations with the multi-spectral solar telescope array Paul Boerner Dissertation thesis Stanford University July 2004 Image from the 211 Å Ritchey-Chrétien telescope Image from the 1216 Å Ritchey-Chrétien telescope

37 Course schedule

38 Animal vision

39 Course schedule

40 Course schedule

41 MRI

42 Course schedule

43

44 Google Earth

45 Reflectance from fresh or dry oak leaf Reflectance spectra of leaves will be different dependent on its state

46 Satellite imaging of forests Photosynthetic activity Average rainfall University of Arizona Terrestial Biophysics and Remote Sensing Lab

47 Course schedule

48 Multivariate analysis Microscopic imaging Microscopy of red blood cells Find which red blood cells that are infected with the malaria parasite

49 Microscopic imaging R S T

50 Multivariate analysis PC1 PC2 PC3

51 Microscopic imaging

52 Course schedule

53 Scanning Probe Microscopy Example: Scanning Tunneling Microscopy

54 Course schedule

55 Home assignments Four home assignments Contrast function (Data analysis lecture) Noise (Data aquisition lecture) Satellite imaging (Satellite imaging lecture) PET/SPECT/X-ray imaging (High-energy imaging lecture)

56 Laboratory exercises Sign up for the labs during lectures on paper! Hand in lab reports (afterwards) Lab reports should be approved before written exam

57 Multispectral imaging from radiowaves to gammarays

58 Multispectral imaging from astronomy to microscopy

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