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--- courses:456:2022:projects:456-2022-16:project-16 [2022/03/02 04:51] – [Background, Specific Aims, and Significance] hishida3
+++ courses:456:2022:projects:456-2022-16:project-16 [2022/05/24 03:10] (current) – [Reports and presentations] hishida3
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 ======VR Guided SurgerySDF based guidance and safety======
-**Last updated: March.1st, 23:30**
+**Last updated: May.17th, 13:20**
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 **Technical Background**\\
-Previous work from Hopkins has developed a virtual simulator, AMBF,  for volumetric drilling. This simulation leverages segmented CT images to create an anatomically accurate drilling simulator environment which the users observe via a stereoscopic display. This simulator is particularly powerful because it allows users to practice surgical procedures while also generating data for surgical computer vision algorithms.
+Previous work from Hopkins has developed a virtual simulator, AMBF[1],  for volumetric drilling. This simulation leverages segmented CT images to create an anatomically accurate drilling simulator environment which the users observe via a stereoscopic display. This simulator is particularly powerful because it allows users to practice surgical procedures while also generating data for surgical computer vision algorithms.
-{{:courses:456:2022:projects:456-2022-16:ambf.png?400|}}
+{{:courses:456:2022:projects:456-2022-16:ambf.png?600|}}
 Currently, the simulation environment does not provide safety cues related to the distance between the drill and critical anatomies. Although a warning message is provided when the user collides with an anatomy, this is not enough feedback to teach the train how to avoid such a dangerous situation in a real procedure. Secondly, the simulator lacks the capability of providing haptic feedback to secure the patient safety. We believe that improving these two aspects will result in improved safety for the patient and reduce the workload of the surgeons.
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 ======Technical Approach======
-This project will be divided into three different phases where each one of the phases addresses a different objective. Phase 1 will be focusing on integrating SDF functions into the drilling simulation for objects that do not change their volume. Phase 2 will be focusing on using the calculated SDF to improve the situational awareness of the user via haptic or visual feedback. The last phase of the project will be concerned with optimizing the calculation of SDF to perform them in real-time.
+To improve the situational awareness and safety,  it is necessary to calculate the distance between the drill tip and the anatomies in real-time. This information can be then utilize to prevent the user from drilling a critical anatomy or just to improve the user's awareness of close critical anatomical structures as he performs the procedure. This distance could be naively calculated by iterating over the voxel representation of the environment after each drill update. This however is a computationally inefficient algorithm that can result in high delays in the system.
+As an alternative, signed distance fields (SDF) can be calculated for each of the anatomies in the simulation. A SDF function will generate a new voxel map in which the voxel's value is the minimum distance between that specific voxel location and the the reference anatomy. After obtaining a SDF for each of the different anatomies in the simulation, the calculation of the minimum distance between the drill tool tip and a specific anatomy can be speed up significantly. The procedure to obtain this distance would only require to query the SDF in the voxel where the drill is currently located. In this regard, SDF functions need to be calculated for all static anatomies at the beginning of the simulation to provided feedback to the user.
+To achieved the goals of project, the work will be divided into three different phases each one with an unique and specific objective. Phase 1 will be focusing on integrating SDF functions into the drilling simulation for objects that do not change their volume. Phase 2 will be focusing on using the calculated SDF to improve the situational awareness of the user via haptic or visual feedback. The last phase of the project will be concerned with optimizing the calculation of SDF to perform them in real-time.
 ===== Phase 1: SDF calculation for static volumes & software integration architecture. =====
-The goal for this phase is to implement SDF calculation functions for objects whose volume is not changing over time, i.e., anatomies that are not being drilled on. Provided that static objects' SDFs do not change, this calculation can be performed once as an initialization step at the beginning of the simulation. Then, the calculated SDFs can be stored in a look-up table to be used while the user is interacting with the simulator. The diagram below summarizes the different components of the proposed system.
+The goal for this phase is to implement SDF calculation functions for static objects whose volume is not changing over time, i.e., critical anatomies that are not being drilled on. For this phase, it will be assumed that the critical anatomies' SDF will be constant through out all the simulation, and therefore, the SDF calculation can be performed only once at initialization. Then, the calculated SDFs can be stored in a look-up table to be used while the user is interacting with the simulator. The diagram below summarizes the different components of the proposed system.
 {{:courses:456:2022:projects:456-2022-16:phase1_tech_approach.png?600|}}
-The implementation of the SDF will be based on the method proposed by Saito and Toriwaki, 1994[2]. This method was chosen because it allows for parallelization of the calculations and works with volumes represented as voxel grids. These functions will be implemented in c++ and compiled as a shared library. Then, the library will be added to the simulation utilizing the AMBF plugins capability.
+The implementation of the SDF will be based on the method proposed by Saito and Toriwaki, 1994\cite{saito_new_1994}. This method was chosen because it allows for parallelization of the calculations and works with volumes represented as voxel grids. These functions will be implemented in c++ and compiled as a shared library. Then, the library will be added to the simulation utilizing the AMBF plugins capability.
 ===== Phase 2: Improved situational awareness of the user by SDF =====
-The goal for this phase is to implement improved situational awareness using different feedback modalities: Visual feedback and Haptic feedback.
+This phase aims to implement helpful feedback with different modalities for surgeons using the SDF look-table calculated in Phase 1. We are currently planning to implement two different feedbacks: visual warning and haptic feedback.
-For visual feedback, our plan is to overlay a warning message saying when the drill gets too close to the important anatomy.
-Using the stored look-up table of SDF for each structure, we can monitor the distance between the drill and the anatomy in real-time.
+For visual warning, a warning message will be overlayed to the screen to provide an intuitive warning to the surgeons. This warning will be initialized when the drill passes a certain threshold using the SDF look-up table. Consequently, our method could provide situational awareness before damaging the important anatomy.
 {{:courses:456:2022:projects:456-2022-16:warning.png?400|}}
-For haptic feedback, we are adopting the virtual fixture method[3]. Our proposal is to provide forbidden regional virtual fixtures to avoid collision with the important anatomy. We will compare the proposed method with the mesh-based VF[4] for the effectiveness of the method.
+For haptic feedback we are adopting the virtual fixture method, specifically the forbidden regional VF[3], to avoid collision with the anatomy using the gradient field of the SDF. Virtual fixtures are reported to be very effective in improving both the accuracy and the safety during the skull drilling experiment[4]
 {{:courses:456:2022:projects:456-2022-16:vf.png?400|}}
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 ===== Phase 3: SDF online implementation =====
-More details for the SDF implementation will be added for finishing Phase 1 of the project. Finishing phase 1 will provide us with information about how fast the algorithms are running in the simulation and how much faster they need to be for optimal performance in real-time. This information will guide the modification of the algorithms for phase 3.
+Technical details of the phase 3, will be specified as soon as the phase 1 is finished. The reason for that is that the speed at which the SDF can be calculated is currently unknown. The speed at which SDFs can be calculated on the static case will determine the modifications required for real-time calculations.
 ======Dependencies======
 describe dependencies and effect on milestones and deliverables if not met
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     *{{ :courses:456:2022:projects:456-2022-16:cis_project_proposal.pdf |Project plan proposal}}
   * Project Background Reading
+    * {{ :courses:456:2022:projects:456-2022-16:cisii_background_reading.pdf |Project Background Reading}}
     * See Bibliography below for links.
   * Project Checkpoint
-    * {{:courses:456:2022:projects:456-2022-01:checkpoint_presentation.pdf| Project checkpoint presentation}}
+    * {{ :courses:456:2022:projects:456-2022-16:checkpoint_presentation.pdf |Project checkpoint presentation}}
-  * Paper Seminar Presentations
+  * Paper Background Presentations
-    * here provide links to all seminar presentations
+    * {{ :courses:456:2022:projects:456-2022-16:cisii_background.pdf |Paper Background Presentations}}
+    * {{ :courses:456:2022:projects:456-2022-16:virtual_reality_for_synergistic_surgical_training_and_data_generation.pdf |Virtual Reality for Synergistic Surgical Training and Data generation}}
+    * {{ :courses:456:2022:projects:456-2022-16:0194599819861526.pdf |Image-Guided Mastoidectomy with a Cooperatively Controlled ENT Microsurgery Robot}}
+  * Project Final written report
+    *{{ :courses:456:2022:projects:456-2022-16:cis_final_project_report.pdf |Final Report}}
   * Project Final Presentation
-    * {{:courses:456:2022:projects:456-2022-01:final_poster_pdf.pdf|PDF of Poster}}
+    * {{ :courses:456:2022:projects:456-2022-16:cisii_final_shortpresentation.pptx |Final Presentation}}
-  * Project Final Report
+  * Project Final Poster
-    * {{:courses:456:2022:projects:456-2022-01:final_report.pdf|Final Report}}
+    * {{ :courses:456:2022:projects:456-2022-16:cisii_finalposter.pptx |Final Poster}}
     * links to any appendices or other material
+  * Code and documentation:
+    * https://github.com/jabarragann/volumetric_drilling/tree/devel
 ======Project Bibliography=======
 [1] A. Munawar et al., “Virtual reality for synergistic surgical training and data generation,” Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, vol. 0, no. 0, pp. 1–9, Nov. 2021, doi: 10.1080/21681163.2021.1999331.

courses/456/2022/projects/456-2022-16/project-16.1646196698.txt.gz · Last modified: 2022/03/02 04:51 by hishida3