Talk:Medical imaging

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3D reconstruction 1st version[edit]

The following content was added in these 2 difs by User:Sam93katoch and User:209.147.144.62

3D Reconstruction of Medical Images'

Clinical routine of diagnosis, patient follow-up, computer assisted surgery, surgical planning etc. are facilitated by accurate 3D models of the desired part of human anatomy. Conventional methods like computed tomography (CT) and Magnetic Resonance Imaging (MRI) have several disadvantages including

  • High Irradiation dose in CT.
  • Horizontal Alignment of patients which changes the global shape of bone structure evident in diseases related to spine and lower limb.
  • Expensive and inappropriate for patients with ferromagnetic metallic implants (MRI).
  • High resolution T1-weighted MRI followed by laborious post-processing steps like segmentation can be difficult in many cases if the patient is not properly aligned in the scanner.

Applications:

3D reconstruction system finds its application in a variety of field including

  • Medicine
  • Film industry
  • Robotics
  • City planning
  • Gaming
  • Virtual environment
  • Earth observation
  • Archaeology
  • Augmented reality
  • Reverse engineering
  • Animation
  • Human computer interaction

Existing Approaches:

Delaunay Triangulation(25 Points)

Delaunay and alpha-shapes

  • Delaunay method involves extraction of tetrahedron surfaces from initial point cloud. The idea of ‘shape’ for a set of points in space is given by concept of alpha-shapes. Given a finite point set S, and the real parameter alpha, the alpha-shape of S is a polytope (the generalization to any dimension of a two dimensional polygon and a three-dimensional polyhedron) which is neither convex nor necessarily connected[1] . For a large value, the alpha-shape is identical to the convex-hull of S. The algorithm proposed by Edelsbrunner and Mucke [2] eliminates all tetrahedrons which are delimited by a surrounding sphere smaller than α. The surface is then obtained with the external triangles from the resulting tetrahedron[2].
  • Another algorithm called Tight Cocone[3] labels the initial tetrahedrons as interior and exterior. The triangles found in and out generate the resulting surface. Both methods have been recently extended for reconstructing point clouds with noise [3]. In this method the quality of points determines the feasibility of the method. For precise triangulation since we are using the whole point cloud set, the points on the surface with the error above the threshold will be explicitly represented on reconstructed geometry[1].

Zero Set Methods

Marching Cubes

Reconstruction of the surface is performed using a distance function which assigns to each point in the space a signed distance to the surface S. A contour algorithm is used to extract a zero-set which is used to obtain polygonal representation of the object. Thus, the problem of reconstructing a surface from a disorganized point cloud is reduced to the definition of the appropriate function f with a zero value for the sampled points and different to zero value for the rest. An algorithm called Marching-Cubes established the use of such methods[4]. There are different variants for given algorithm, some use a discrete function f, while other use a polyharmonic radial basis function which is used to adjust the initial point set[5][6]. Functions like Moving Least Squares, basic functions with local support[7], based on the Poisson equation have also been used. Loss of the geometry precision in areas with extreme curvature, i.e., corners, edges is one of the main issues encountered. Furthermore, pretreatment of information, by applying some kind of filtering technique, also affects the definition of the corners by softening them. There are several studies related to post-processing techniques used in the reconstruction for the detection and refinement of corners but these methods increase the complexity of the solution[8].

3D Maximum Intensity Projection

VR Technique

Entire volume transparence of the object is visualized using VR (volume rendering) technique. Images will be formed by projecting rays through volume data. Along each ray, at every voxel, opacity and color needs to be calculated. Then information calculated along each ray will to be aggregated to a pixel on image plane. An entire compact structure of the object can be viewed comprehensively . Since the technique needs enormous amount of calculations, which requires strong configuration computers it is appropriate for low contrast data. Two main methods[9] for rays projecting can be considered as follows:

  • Object-order method: Projecting rays go through volume from back to front (from volume to image plane).
  • Image-order or ray-casting method: Projecting rays go through volume from front to back (from image plane to volume).There exists some other methods to composite image, appropriate methods depending on the user’s purposes. Some usual methods in medical image are MIP (maximum intensity projection), MinIP (minimum intensity projection), AC (alpha compositing) and NPVR (non-photorealistic volume rendering).

Voxel Grid

High Resolution Intravital Microscopy

In this filtering technique input space is sampled using a grid of 3D voxels to reduce the number of points[10]. For each voxel, a centroid is chosen as the representative of all points. There are two approaches, the selection of the voxel centroid or select the centroid of the points lying within the voxel. To obtain internal points average has a higher computational cost, but offers better results. Thus, a subset of the input space is obtained that roughly represents the underlying surface. The Voxel Grid method presents the same problems as other filtering techniques: impossibility of defining the final number of points that represent the surface, geometric information loss due to the reduction of the points inside a voxel and sensitivity to noisy input spaces. 

References

  1. ^ a b Angelopoulou, Anastassia; Psarrou, Alexandra; Garcia-Rodriguez, Jose; Orts-Escolano, Sergio; Azorin-Lopez, Jorge; Revett, Kenneth. "3D reconstruction of medical images from slices automatically landmarked with growing neural models". Neurocomputing. Volume 150, Part A, 20 February 2015, Pages 16-25, ISSN 0925-2312, http://dx.doi.org/10.1016/j.neucom.2014.03.078. 
  2. ^ a b Edelsbrunner, Herbertr; P. Mücke, Ernst. "Three-dimensional alpha shapes". ACM Transactions on Graphics (TOG). Volume 13 Issue 1, Jan. 1994 Pages 43-72. 
  3. ^ K. Dey, Tamal; Goswami, Samrat. "Probable surface reconstruction from noisy samples". Comput. Geom. 35 (2006) 124–141. 
  4. ^ E. Lorensen, William; E. Cline, Harvey. "Marching cubes: A high resolution 3D surface construction algorithm". ACM SIGGRAPH Computer Graphics. Volume 21 Issue 4, July 1987 Pages 163-169. 
  5. ^ Hoppe, Hugues; DeRose, Tony; Duchamp, Tom; McDonald, John; Stuetzle, Werner. "Surface reconstruction from unorganized points". SIGGRAPH Comput. Graph. 26 (July (2)) (1992), pp. 71–78. 
  6. ^ Carr, J.C.; Beatson, R.K.; Cherrie, J.B.; Mitchell, T.J.; Fright, W.R.; McCallum, B.C.; Evans, T.R. "Reconstruction and representation of 3d objects with radial basis functions". 28th Annual Conference on Computer Graphics and Interactive Techniques, SIGGRAPH ׳01,ACM, New York, NY, USA. 2001, pp. 67–76. 
  7. ^ Walder, C.; Schlkopf, B.; Chapelle, O. "Implicit surface modelling with a globally regularised basis of compact support". EUROGRAPHICS. 2006. 
  8. ^ Wang, Charlie C. L. "Incremental reconstruction of sharp edges on mesh surfaces". Computer-Aided Design. Volume 38 Issue 6, June, 2006 Pages 689-702. 
  9. ^ Wallis, J.W.; TR, Miller. "Volume rendering in three-dimensional display of SPECT images". Journal of nuclear medicine. 31 (8): 1421–8. 
  10. ^ Connolly, C. "Cumulative generation of octree models from range data". Robotics and Automation. 1984, pp. 25–32. 

I removed this with edit note WP:CRYSTALBALL, as this is all research, an not actual medical imaging used clinically, as far as I know (and the sources and content don't make that clear). It is also too WP:TECHNICAL. It also given a lot of space, which seems WP:UNDUE to me.

Additionally... the introduction contrasts this to MRI and CT but doesn't make clear what kind of actual acquisition technology is used; no acquisition technology is perfect. So what generates the data used here?

The sources are also old, and primary, not secondary. (see WP:MEDDEF). A bunch of this also cites no sources at all.

So those are six issues CRYSTALBALL, TECHNICAL, UNDUE, missing information to provide context, and sourcing or lack thereof. Jytdog (talk) 03:17, 16 November 2016 (UTC)

3D reconstruction 2nd version[edit]

Content was then re-added by User:Ksaikeerthy in these diffs:

Projection of P on both cameras
3D reconstruction of medical images
Motivation & applications

The 2-D imaging has problems of anatomy overlapping with each other and don’t disclose the abnormalities. The 3-D imaging can be used for both diagnostic and therapeutic purposes.

3-D models are used for planning the operation, morphometric studies and has more reliability in orthopedics.

Problem statement & Basics

To reconstruct 3-D images from 2-D images taken by a camera at multiple angles.

Lateral view of the bone

Medical imaging techniques like CT scan and MRI are expensive. Though CT scan is accurate, it induces high radiation dose which is a risk for patients with certain diseases. Methods based on MRI are not accurate. Since we are exposed to powerful magnetic field, this method is not suitable for patients with ferromagnetic metallic implants. Both the methods can be done only when in lying position where the global structure of the bone changes. So, we discuss the following methods which can be performed while standing and require low radiation dose.

Though these techniques are 3-D imaging, the region of interest is restricted to a slice, data is acquired to form a time sequence. 

1) Stereo Corresponding Point Based Technique

This method is simple and implemented by identifying the points manually in multi-view radiographs. The first step is to extract the corresponding points in two x-ray images and second step is the 3D reconstruction with algorithms like Discrete Linear Transform [1]. Using DLT, the reconstruction is done only where there are SCP’s. By increasing the number of points , the results improve [2]but it is time consuming. This method has low accuracy because of low reproducibility and time consumption. This method is dependent on the skill of the operator. This method is not suitable for bony structures with continuous shape. This method is generally used as intial solution for other methods[3].

anterier view of the bone
2) Non-Stereo corresponding contour method(NCSS)

This method uses X-ray images for 3D Reconstruction and to develop 3D models with low dose radiations in weight bearing positions.

In NSCC algorithm, the preliminary step is calculation of an initial solution. Firstly anatomical regions from the generic object are defined. Secondly, manual 2D contours identification on the radiographs is performed. From each radiograph 2D contours are generated using the 3D initial solution object. 3D contours of the initial object surface are projected onto their associated radiograph [3]. The 2D association performed between these 2 set points is based on point-to-point distances and contours derivations developing a correspondence between the 2D contours and the 3D contours. Next step is optimization of the initial solution. Lastly deformation of the optimized solution is done by applying Kriging algorithm to the optimized solution [4]. Finally, by iterating the final step until the distance between two set points is superior to a given precision value the reconstructed object is obtained. 

The advantage of this method is they can be used for bony structures with continuous shape and it also reduced human intervention but they are time consuming.

posterier view of the bone
3) Surface Rendering technique 

Surface Rendering technique visualizes a 3D object as a set of surfaces called iso-surfaces. Each surface has points with same intensity (called iso-value). It is used when we want to see the separated structures e.g. skull from slices of head, blood vessel system from slices of body etc. This technique is used mostly for high contrast data. Two main methods for reconstructing are:

- Contour based reconstruction: Iso-contours are attached to form iso-surfaces [5] .

- Voxel based reconstruction: Voxels having same intensity values are used to form iso-surfaces. One of the best algorithms is Marching Cubes [5] . Some similar algorithms as Marching Tetrahedrons, Deviding Cubes [5] can be considered.

Other methods which can be used for 3d reconstruction are

Other proposed or developed techniques include Statistical Shape Model Based Methods, Parametric Methods, Hybrid methods.

References

  1. ^ "Pearcy MJ. 1985. Stereo radiography of lumbar spine motion. Acta Orthop Scand Suppl" (PDF). 
  2. ^ "Aubin CE, Dansereau J, Parent F, Labelle H, de Guise JA. 1997. Morphometric evaluations of personalised 3D reconstructions and geometric models of the human spine". Med Biol Eng Comput. 
  3. ^ a b "S.Hosseinian, H.Arefi, 3D Reconstruction from multiview medical X-ray images- Review and evaluation of existing methods." (PDF). 
  4. ^ "Laporte S, Skalli W, de Guise JA, Lavaste F, Mitton D.2003. A biplanar reconstruction method based on 2D and 3D contours: application to distal femur". Comput Methods Biomech Biomed Engin. 
  5. ^ a b c G.Scott Owen, HyperVis. ACM SIGGRAPH Education Committee, the National Science Foundation (DUE-9752398), and the Hypermedia and Visualization Laboratory, Georgia State University. 

This is shorter than the first version, so less of an issue with UNDUE, but all the other issues mentioned above are still present.

Also are you all in a class or something? Please explain what is going on. Thanks. Jytdog (talk) 03:19, 16 November 2016 (UTC)

Hey guys,

This is my first time to edit a wiki page. Yes, this was a course assignment. So we are waiting for a feedback from our professor. As soon as I get that I will make the necessary changes. And I also read your viewpoints on the topic and hence will research over the matter more so as to improve it. (Sam93katoch (talk) 04:21, 16 November 2016 (UTC))

Moreover since our course assignment included that we have to write the approaches on which research is going on, thats why I included those methods. But I will try to cite better publications for the same.(Sam93katoch (talk) 04:25, 16 November 2016 (UTC))

Thanks for replying!! Before you take a second shot, please do review the training materials at the links that I left on your talk page. Content in Wikipedia needs to be comply with the policies and guidelines that the community put in place over the years - there is a learning curve. Not impossible, but there is stuff you have to be grounded on. Jytdog (talk) 04:59, 16 November 2016 (UTC)

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External links modified[edit]

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