Augmented reality for narrow area navigation in jaw surgery: Modified tracking by detection volume subtraction algorithm.

BACKGROUND AND AIM: Jaw surgery based on augmented reality (AR) still has limitations in terms of navigating narrow areas. Surgeons need to avoid nerves, vessels, and teeth in their entirety, not just root canals. Inaccurate positioning of the surgical instrument may lead to positional or navigational errors and can result in cut blood vessels, nerve channels, or root canals. This research aims to decrease the positional error during surgery and improve navigational accuracy by reducing the positional error. METHODOLOGY: The proposed 2D/3D system tracks the surgical instrument, consisting of the shaft and the cutting element, each part being assigned a different feature description. In the case of the 3D position estimation, the input vector is composed of image descriptors of the instrument and the output value consists of 3D coordinates of the cutter. RESULTS: Sample results from a jawbone-maxillary and mandibular jaw-demonstrate that the positional error is reduced. The system, thus, led to an improvement in alignment of the video accuracy by 0.25 to 0.35 mm from 0.40 to 0.55 mm and a decrease in processing time of 11 to 14 frames per second (fps) against 8 to 12 fps of existing solutions. CONCLUSION: The proposed system is focused on overlaying only on the area to be operated on. Thus, this AR-based study contributes to accuracy in navigation of the deeper anatomical corridors through increased accuracy in positioning of surgical instruments.

A novel rotation invariant and Manhattan metric-based pose refinement: Augmented reality-based oral and maxillofacial surgery.

BACKGROUND: Augmented reality (AR) is gaining attention in medicine because of the convenience and innovation that it brings to operating rooms. Furthermore, oral and maxillofacial surgery (OMS), which is one of sensitive and narrow spatial surgery, requires high accuracy in image registration and low processing time of the system. However, the current systems are suffering from image registration problems while matching two different posture images. We thus aimed to increase that overlay accuracy and decrease the processing time. METHODOLOGY: The proposed system consists of an Iterative Closest Point (ICP) algorithm, which is the combination of a rotation invariant and Manhattan error metric, to provide the best initial parameters and to decrease the computational cost by sorting high and low processing pixel images, respectively. RESULT: The study on maxillary and mandibular jaw bone demonstrates that the proposed work overlay accuracy ranges from 0.22 to 0.30 mm, and processing time ranges from 10 to 14 frames per second as opposed to the 0.23- to 0.35-mm overlay accuracy and the current 8 to 12 frames per second processing time. CONCLUSION: This research aimed to improve the visualization and fast AR system for the OMS. Thus, the proposed system achieved an improvement in overlay accuracy and processing time by implementing the Rotation Invariant and Manhattan error metric ICP algorithm.

A novel augmented reality to visualize the hidden organs and internal structure in surgeries.

BACKGROUND: Augmented reality (AR) is still a primarily theoretical concept in areas such as bowel, liver, gallbladder, and jaw surgeries because of the limitation of visualization accuracy of hidden organs and internal structures. This paper aims to improve the cutting accuracy, visualizing accuracy, and processing time of the augmented video. METHODOLOGY: The proposed system consists of an enhanced block-matching algorithm (BMA) with ghosting map technique. RESULTS: Results proved that proposed system reduced the visualization error, which ranges from 1.48 to 1.83 mm against the existing system visualization error 1.67 to 2.0. Similarly, the processing time also improved 59 to 72 ms/frame over the 50 to 58 ms/frame. CONCLUSION: This study showed the improvement and solved the problem soft tissue reconstruction and visualization on the AR video that used in bowel and gallbladder surgeries.

A novel mixed reality in breast and constructive jaw surgical tele-presence.

BACKGROUND AND AIM: Surgical telepresence has been implemented using Mixed reality (MR) but, MR is theory based and only used for investigating research. The Aim of this paper is to propose and implement a new solution by merging augmented video (generating in local site) and virtual expertise surgeon hand (remote site). This system is to improve the visualization of surgical area, overlay accuracy in the merged video without having any discoloured patterns on hand, smudging artefacts on surgeon hand boundary and occluded areas of surgical area. METHODOLOGY: The Proposed system consists of an Enhanced Multi-Layer Mean Value Cloning (EMLMV) algorithm that improves the overlay accuracy, visualization accuracy and the processing time. This proposed algorithm includes trimap and alpha matting as a pre-processing stage of merging process, which helps to remove the smudging and discoloured artefacts surrounded by remote surgeon hand. RESULTS: Results showing that the proposed system improved the accuracy by reducing the overlay error of merging image from 1.3 mm (Millimeter) to 0.9 mm. Furthermore, it improves the visibility of surgeon hand in the final merged image from 98.4% (visibility of pixels) to 99.1% (visibility of pixels). Similarly, the processing time in our proposed solution is reduced, which is computed as 10 s to produce 50 frames, whilst, the state of art solution computes 11 s for the same number of frames. CONCLUSION: The proposed system focuses on the merging of augmented reality video (local site), and the virtual reality video (remote site) with the accurate visualization. we consider discoloured areas, smudging artefacts and occlusion as the main aspects to improve the accuracy of merged video in terms of overlay error and visualization error. So, the proposed system would produce the merged video with the removal of artefacts around the expert surgeon hand.

A novel multiple communication paths for surgical telepresence videos delivery of the maxilla area in oral and maxillofacial surgery.

PURPOSE: A surgical telepresence between two surgical sites where a local surgeon in the surgery site, who is less experienced, needs help from the expert surgeon located at a remote site. Furthermore, the primary aim of this paper is to improve the quality of surgical video sent and received to-and-from both surgical sites, which has been a major quality issue so far. METHOD: This work considers flow rate allocation and resource availability to determine the network path quality. Furthermore, a segmented backup path is used to provide a timely recovery in case of failure in the link. A neighbour detection technique in segmented backup is used to reduce the detection latency of the network in case of link failure. RESULTS: The results depict that the proposed system improves the quality of the surgical video by an average of 5.5 db over the current system. Furthermore, the neighbour detection technique detects the network failure 40-45% faster than the currently used end-to-end detection system. The experimental results have done on the maxilla areas in oral and maxillofacial surgery. CONCLUSION: The proposed system concentrates on reducing the network failure detection latency and improves the received and sent video quality by using an enhanced path quality technique. Thus, this study enhances the video quality and provides a backup option in case of failure, which offers timely recovery for communication between two surgeons.

A novel rotational matrix and translation vector algorithm: geometric accuracy for augmented reality in oral and maxillofacial surgeries.

BACKGROUND: Augmented reality-based surgeries have not been successfully implemented in oral and maxillofacial areas due to limitations in geometric accuracy and image registration. This paper aims to improve the accuracy and depth perception of the augmented video. METHODOLOGY: The proposed system consists of a rotational matrix and translation vector algorithm to reduce the geometric error and improve the depth perception by including 2 stereo cameras and a translucent mirror in the operating room. RESULTS: The results on the mandible/maxilla area show that the new algorithm improves the video accuracy by 0.30-0.40 mm (in terms of overlay error) and the processing rate to 10-13 frames/s compared to 7-10 frames/s in existing systems. The depth perception increased by 90-100 mm. CONCLUSION: The proposed system concentrates on reducing the geometric error. Thus, this study provides an acceptable range of accuracy with a shorter operating time, which provides surgeons with a smooth surgical flow.