Surgical skills can be improved by continuous surgical training and feedback, thus reducing adverse outcomes while performing an intervention. With the advent of new technologies, researchers now ...have the tools to analyze surgical instrument motion to differentiate surgeons’ levels of technical skill. Surgical skills assessment is time-consuming and prone to subjective interpretation. The surgical instrument detection and tracking algorithm analyzes the image captured by the surgical robotic endoscope and extracts the movement and orientation information of a surgical instrument to provide surgical navigation. This information can be used to label raw surgical video datasets that are used to form an action space for surgical skill analysis. Instrument detection and tracking is a challenging problem in MIS, including robot-assisted surgeries, but vision-based approaches provide promising solutions with minimal hardware integration requirements. This study offers an overview of the developments of assessment systems for surgical intervention analysis. The purpose of this study is to identify the research gap and make a leap in developing technology to automate the incorporation of new surgical skills. A prime factor in automating the learning is to create datasets with minimal manual intervention from raw surgical videos. This review encapsulates the current trends in artificial intelligence (AI) based visual detection and tracking technologies for surgical instruments and their application for surgical skill assessment.
Purpose
Image segmentation of instruments in the raw surgical videos is a critical component of intraoperative assistance softwares. Challenges include addressing rendered overlays occluding the ...instrument while providing pivotal input to instrument tracking frameworks and, train the segmentation process with limited labelled data available from surgical videos.
Method
The proposed adversarial network, InstruSegNet uses unpaired training (eliminating need for massive paired data) for automated multi‐class surgical instrument segmentation in raw surgical videos with complex backgrounds. The proposed method is applied for single/multiple robotic and rigid instruments and optimised on least square Generative Adversarial Networks loss.
Result
Promising validation has been conducted on the publicly available dataset. Proposed approach for multi‐class segmentation of robotic and rigid instruments meets outstanding performance in terms of accuracy and surpasses the existing methods.
Application
This work facilitates segmenting instrument information without manual interventions from raw videos providing means to code surgeon's actions for developing intelligent assistance software.
•A novel network architecture RescueNet is proposed for brain tumor segmentation.•An unpaired GAN based training approach is proposed to train the RescueNet.•Scale-invariant post-processing algorithm ...is proposed to enhance the accuracy.•Performance of the proposed network is tested on BraTS-2015 and BraTS-2017 dataset.
Even with proper acquisition of brain tumor images, the accurate and reliable segmentation of tumors in brain is a complicated job. Automatic segmentation become possible with development of deep learning algorithms that brings plethora of solutions in this research prospect. In this paper, we designed a network architecture named as residual cyclic unpaired encoder-decoder network (RescueNet) using residual and mirroring principles. RescueNet uses unpaired adversarial training to segment the whole tumor followed by core and enhance regions in a brain MRI scan. The problem in automatic brain tumor analysis is preparing large scale labeled data for training of deep networks which is a time consuming and tedious task. To eliminate this need of paired data we used unpaired training approach to train the proposed network. Performance evaluation parameters are taken as DICE and Sensitivity measure. The experimental results are tested on BraTS 2015 and BraTS 2017 1 dataset and the result outperforms the existing methods for brain tumor segmentation. The combination of domain-specific segmentation methods and general-purpose adversarial learning loomed to leverage huge advantages for medical imaging applications and can improve the ability of automated algorithms to assist radiologists.
Path planning of a tool in Minimally Invasive Surgery (MIS) can provide assistance to the surgeons by giving solutions for faster and safe tool movements during the surgery. However, the main ...challenge in this problem is to address non-uniform tool shape for planning that can change due to the tool's dexterity. A typical robotic path planning approach by describing the robot's feasible movements using C-space is applied in this work. Unlike the robotic path planning problem, the C-space description capturing the movement does not give any closed-form solution due to high degree of freedom associated with the tool moved by human hands. Hence, an interval-based approach is used for describing the C-space. The proposed interval-based approach is capable of dividing the space into feasible and non-feasible intervals of different sizes which helps to reduce the search area and cover the obstacles in a refined manner. This paper presents collision-free and fast path computation using interval arithmetic between any two points in a 2D- surgical environment cluttered with obstacles for a surgical tool robot.
This paper tackles instrument tracking and 3D visualization challenges in minimally invasive surgery (MIS), crucial for computer-assisted interventions. Conventional and robot-assisted MIS encounter ...issues with limited 2D camera projections and minimal hardware integration. The objective is to track and visualize the entire surgical instrument, including shaft and metallic clasper, enabling safe navigation within the surgical environment. The proposed method involves 2D tracking based on segmentation maps, facilitating creation of labeled dataset without extensive ground-truth knowledge. Geometric changes in 2D intervals express motion, and kinematics based algorithms process results into 3D tracking information. Synthesized and experimental results in 2D and 3D motion estimates demonstrate negligible errors, validating the method for labeling and motion tracking of instruments in MIS videos. The conclusion underscores the proposed 2D segmentation technique's simplicity and computational efficiency, emphasizing its potential as direct plug-in for 3D visualization in instrument tracking and MIS practices.
Mobile devices with oodles of interfaces communicating concurrently through multi-homed access networks with a blend of wired and wireless transmission parameters need efficient data delivery. To ...suffice the need this paper investigates the impact of various retransmission policies, viz. RTX-SAME, RTX-ASAP, RTX-LOSSRATE, RTX-SSTRESH, RTX-CWND, AllRtxSame, AllRtxAlt and FrSameRtoAlt on the throughput of concurrent multipath transfers (CMT). The performance analysis for the first five policies being extended with partial reliability extension of Stream Control Transmission Protocol (PR-SCTP). The simulation was conducted using NS-2.35 on a multi-homed heterogeneous network with wired links and WiMAX, 3G, 4G and 5G specifications supporting wireless links. The paper validates that among the five basic retransmission policies RTX-ASAP performs best both for CMT using SCTP and for CMT using PR-SCTP. AllRtxAlt performs best for aggressive fail over case under dissimilar path loss rates.
Puran is a stuffing of puran poli (sweet flat bread)—an Indian traditional cuisine made from the mixture of cooked chickpea splits and jaggery. Instant puran powder (IPP) was made by hot air drying ...(HAD) and vacuum drying (VD) at different temperatures (40, 50, and 60°C) to reduce the preparation time of puran. Different semi‐empirical models were fitted to the drying data and Page model was found to suitably explain the experimental data. The highest water absorption index, water solubility index, rehydration ratio, lightness, firmness, and overall acceptability were found in case of vacuum dried IPP produced at 60°C. Browning index, a*, and b* of vacuum dried IPP at 60°C were the lowest. In vitro protein digestibility and minerals were not significantly affected by the drying method. Highest moisture diffusivity (7.24 × 10−09 m2/s) and lowest activation energy (70.28 kJ/mol) were found in IPP dried by VD at 60°C.
Practical applications
Results of this investigation would facilitate food industries in developing efficient and robust process condition for puran manufacturing. This study is the first report that deals with the physico‐functional properties and drying characteristics of puran. Moreover, models generated in this work for moisture mapping of the product provide vital information for engineering control systems. Vacuum drying technology for puran at 60°C was found the most suitable for commercial preparation of puran powder.
