author = {F. P. Vidal and M. Folkerts and N. Freud and S. Jiang},
  title = {{GPU} Accelerated {DRR} Computation with Scatter},
  journal = {Medical Physics},
  year = 2011,
  volume = 38,
  pages = {3455-3456},
  number = 6,
  month = jul,
  address = {Vancouver, Canada},
  annotation = {AAPM Annual Meeting, Jul~31--Aug~4, 2011},
  abstract = {Purpose: We propose a fast software library implemented on 
	graphics processing unit (GPU) to compute digitally reconstructed 
	radiographs (DRRs). It takes into account first order Compton 
	Methods: The simulation is based on the evaluation of 
	the Beer-Lambert law and of the Klein-Nishina equation. The 
	algorithm is fully determinist and has been fully implemented on 
	GPU to achieve clinically acceptable efficiency. A full resolution 
	simulation is performed for primary radiation. A much lower image 
	resolution is used for Compton scattering as it adds a low frequency 
	pattern over the projection image. Each voxel of the CT dataset is 
	considered as a secondary source. The number of photons that reach 
	each voxel is evaluated. Then, for each secondary source, a projection 
	image is computed and integrated in the final image. The photon energy 
	between each secondary source and each pixel is also computed. 
	An interlaced sampling mode is also proposed to further reduce 
	the computation time without sacrificing numerical accuracy. Finally, 
	the speed and accuracy are assessed.
	Results: We show that the computations can be fully implemented on 
	the GPU with an original under-sampling method to produce clinically 
	acceptable results. For example, a simulation can be achieved in less 
	than 7 seconds whilst the maximum relative error remains below 5\% and
       	the average relative error below 1.4\%. At full resolution, a speed-up 
	by factor ∼12X is achieved for the GPU implementation with our 
	interlaced-mode by comparison with our multi-threaded CPU implementation 
	using 8 threads in parallel. 
	Conclusions: DRR calculation with scatter is 
	computationally intensive. The use of GPU can achieve clinically 
	acceptable efficiency. A Compton fluence map can be computed in a few 
	seconds using under-sampling, whilst keeping numerical inaccuracies 
	relatively low. This work can be used for CBCT reconstruction to reduce 
	scatter artifacts.},
  doi = {10.1118/1.3611828},
  publisher = {American Association of Physicists in Medicine}
  author = {F. P. Vidal and J. Louchet and {J.-M.} Rocchisani and \'E. Lutton},
  title = {Flies for {PET}: An Artificial Evolution Strategy for Image Reconstruction in Nuclear Medicine},
  journal = {Medical Physics},
  year = 2010,
  volume = 37,
  pages = {3139},
  number = 6,
  month = jul,
  address = {Philadelphia, Pensilvania, USA},
  annotation = {AAPM Annual Meeting, Jul~18--22, 2010},
  abstract = {Purpose: We propose an evolutionary approach for image 
	reconstruction in nuclear medicine. Our method is based on 
	a cooperative coevolution strategy (also called Parisian evolution): 
	the ``fly algorithm''. 
	Method and Materials: Each individual, or fly, 
	corresponds to a 3D point that mimics a radioactive emitter, i.e. 
	a stochastic simulation of annihilation events is performed to compute 
	the fly's illumination pattern. For each annihilation, a photon is 
	emitted in a random direction, and a second photon is emitted in 
	the opposite direction. The line between two detected photons is 
	called line of response (LOR). If both photons are detected by 
	the scanner, the fly's illumination pattern is updated. 
	The LORs of every fly are aggregated to form the population total 
	illumination pattern. Using genetic operations to optimize the position 
	of positrons, the population of flies evolves so that the population 
	total pattern matches measured data. The final population of flies 
	approximates the radioactivity concentration. 
	Results: We have developed numerical phantom models to assess 
	the reconstruction algorithm. To date, no scattering and no tissue attenuation 
	have been considered. Whilst this is not physically correct, it allows us 
	to test and validate our approach in the simplest cases. 
	Preliminary results show the validity of this approach in both 2D and 
	fully-3D modes. In particular, the size of objects, and 
	their relative concentrations can be retrieved in the 2D mode. 
	In fully-3D, complex shapes can be reconstructed. 
	Conclusions: An evolutionary approach for PET reconstruction has been proposed 
	and validated using simple test cases. Further work will therefore include 
	the use of more realistic input data (including random events and scattering), 
	which will finally lead to implement the correction of scattering within our algorithm. 
	A comparison study against ML-EM and/or OS-EM methods will also need to be conducted.},
  doi = {10.1118/1.3468200},
  publisher = {American Association of Physicists in Medicine},
  pdf = {pdf/Vidal2010MedPhys-A.pdf}
  author = {F. P. Vidal and P. F. Villard and M. Garnier and N. Freud and J. M. L\'etang and N. W. John and F. Bello},
  title = {Joint Simulation of Transmission X-ray Imaging on {GPU} and Patient's Respiration on {CPU}},
  journal = {Medical Physics},
  year = 2010,
  volume = 37,
  pages = {3129},
  number = 6,
  month = jul,
  address = {Philadelphia, Pensilvania, USA},
  annotation = {AAPM Annual Meeting, Jul~18--22, 2010},
  abstract = {Purpose: We previously proposed to compute the X-ray attenuation 
	from polygons directly on the GPU, using OpenGL, to significantly 
	increase performance without loss of accuracy. The method has been 
	deployed into a training simulator for percutaneous transhepatic 
	cholangiography. The simulations were however restricted to 
	monochromatic X-rays using a point source. They now take into account 
	both the geometrical blur and polychromatic X-rays. 
	Method and Materials: To implement the Beer-Lambert law with a 
	polychromatic beam, additional loops have been included in the 
	simulation pipeline. It is split into rendering passes and uses frame 
	buffer objects to store intermediate results. The source shape is 
	modeled using a variable number of point sources and the incident beam 
	is split into discrete energy channels. The respiration model is composed 
	of ribs, spine, lungs, liver, diaphragm and the external skin. The organ 
	motion simulation is based on anatomical and physiological studies: 
	the model is monitored by two independent active components: 
	the ribs with a kinematics law and the diaphragm tendon with an up and 
	down translation. Other soft-tissue components are passively deformed 
	using a 3D extension of the ChainMail algorithm. The respiration rate 
	is also tunable to modify the respiratory profile. 
 	Results: We have extended the simulation pipeline to take into account 
	focal spots that cause geometric unsharpness and polychromatic X-rays, 
	and dynamic polygon meshes of a breathing patient can be used as input data. 
	Conclusions: X-ray transmission images can be fully simulated on the GPU, 
	by using the Beer-Lambert law with polychromatism and taking into account 
	the shape of the source. The respiration of the patient can be 
	modeled to produce dynamic meshes. This is a useful development to improve 
	the level of realism in simulations, when it is needed to retain both speed 
	and accuracy.},
  doi = {10.1118/1.3468154},
  publisher = {American Association of Physicists in Medicine},
  pdf = {pdf/Vidal2010MedPhys-B.pdf}
  author = {A. Sinha and K. Flood and D. Kessel and S. Johnson and C. Hunt and H. Woolnough and F. P. Vidal and {P.-F.} Villard and R. Holbray and C. M. Crawshaw and A. Bulpitt and N. W. John and F. Bello and R. Phillips and D. A. Gould},
  title = {The Role of Simulation in Medical Training and Assessment},
  booktitle = {Radiological Society of North America 2009 (RSNA 2009)},
  year = 2009,
  month = nov,
  address = {Chicago, Illinois},
  annotation = {Nov~29--Dec~4, 2009}
  author = {{P.-F.} Villard and F. P. Vidal and C. Hunt and F. Bello and N. W. John and S. Johnson and D. A. Gould},
  title = {Percutaneous Transhepatic Cholangiography Training Simulator with Real-time Breathing Motion},
  booktitle = {Proceeding of the 23rd International Congress of Computer Assisted Radiology and Surgery},
  year = 2009,
  series = {International Journal of Computer Assisted Radiology and Surgery},
  volume = {4 (Suppl 1)},
  pages = {S66-S67},
  month = jun,
  address = {Berlin, Germany},
  annotation = {Jun~23--27, 2009},
  keywords = {Interventional radiology, Virtual environments, Respiration simulation, X-ray simulation, Needle puncture, Haptics, Task analysis},
  doi = {10.1007/s11548-009-0326-x},
  publisher = {Springer}

This file was generated by bibtex2html 1.97.