Optimized Identification with Severity Factors of Gastric Cancer for Internet of Medical Things

The Internet of Medical Things (IoMT) emerges with the visionof the Wireless Body Sensor Network (WBSN) to improve the health monitoringsystems and has an enormous impact on the healthcare system forrecognizing the levels of risk/severity factors (premature diagnosis, treatment,and supervision of chronic disease i.e., cancer) via wearable/electronic healthsensor i.e., wireless endoscopic capsule. However, AI-assisted endoscopy playsa very significant role in the detection of gastric cancer. Convolutional NeuralNetwork (CNN) has been widely used to diagnose gastric cancer based onvarious feature extraction models, consequently, limiting the identificationand categorization performance in terms of cancerous stages and gradesassociated with each type of gastric cancer. This paper proposed an optimizedAI-based approach to diagnose and assess the risk factor of gastric cancerbased on its type, stage, and grade in the endoscopic images for smarthealthcare applications. The proposed method is categorized into five phasessuch as image pre-processing, Four-Dimensional (4D) image conversion,image segmentation, K-Nearest Neighbour (K-NN) classification, and multigradingand staging of image intensities. Moreover, the performance of theproposed method has experimented on two different datasets consisting ofcolor and black and white endoscopic images. The simulation results verifiedthat the proposed approach is capable of perceiving gastric cancer with 88.09%sensitivity, 95.77% specificity, and 96.55% overall accuracy respectively.

A novel intelligent chromo capsule endoscope for the diagnosis of neoplastic lesions in the gastrointestinal tract

Background:Chromoendoscopy has not been fully integrated into capsule endoscopy.This study aimded to develop and validate a novel intelligent chromo capsule endoscope(ICCE).Methods:The ICCE has two modes:a white-light imaging(WLI)mode and an intelligent chromo imaging(ICI)mode.The performance of the ICCE in observing colors,animal tissues,and early gastrointestinal(GI)neoplastic lesions in humans was evaluated.Images captured by the ICCE were analysed using variance of Laplacian(VoL)values or image contrast evaluation.Results:For color observation,conventional narrow-band imaging endoscopes and the ICI mode of the ICCE have similar spectral distributions.Compared with the WLI mode,the ICI mode had significantly higher VoL values for animal tissues(2.15461.044 vs 3.80061.491,P=0.003),gastric precancerous lesions and early gastric cancers(2.24260.162 vs 6.64260.919,P<0.001),and colon tumors(3.89661.430 vs 11.88267.663,P<0.001),and significantly higher contrast for differentiating tumor and non-tumor areas(0.06960.046 vs 0.14460.076,P=0.005).More importantly,the sensitivity,specificity,and accuracy of the ICI mode for early GI tumors were 95.83%,91.67%,and 94.64%,respectively,which were significantly higher than the values of the WLI mode(78.33%[P<0.001],77.08%[P=0.01],and 77.98%[P<0.001],respectively).Conclusions:We successfully integrated ICI into the capsule endoscope.The ICCE is an innovative and useful tool for differential diagnosis based on contrast-enhanced images and thus has great potential as a superior diagnostic tool for early GI tumor detection.

Smart Image Sensor with Integrated Low Complexity Image Processing for Wireless Endoscope Capsules

A smart image sensor was developed which integrates a digital pixel image sensor array with an image processor, designed for wireless endoscope capsules. The camera-on-a-chip architecture and its on-chip functionality facilitate the design of the packaging and power consumption of the integrated capsule. The power reduction techniques were carried out at both the architectural and circuit level. Gray coding and power gating in the sensor array to eliminate almost 50% of the switch activity on the data bus and more than 99% of the power dissipation in each pixel at a transmitting rate of 2 frames per second. Filtering and compression in the processor reduces the data transmission by more than 2/3. A parallel fully pipelined architecture with a dedicated clock management scheme was implemented in the JPEG-LS engine to reduce the power consumption by 15.7%. The smart sensor has been implemented in 0.18 μm CMOS technology.

Development of a Wireless Capsule Endoscope System Based on Field Programmable Gate Array

A new modular and programmable wireless capsule endoscope is presented in this paper. The capsule system consumes low power and has small physical size. A new image compression algorithm is presented in this paper to reduce power consumption and silicon area. The compression algorithm includes color space transform,uniform quantization, sub-sampling, differential pulse code modulation(DPCM) and Golomb-Rice code. The algorithm is tested in a field programmable gate array(FPGA) development board, and the final result achieves 80% compression rate at 40 dB peak signal to noise ratio(PSNR). The algorithm has high image compression efficiency and low power consumption, compared to other existing works. The system is composed of the following three parts: image capsule endoscope, portable wireless receiver and host computer software. The software and hardware design of the three parts are disscussed in details.

Magnetic Actuation Systems and Magnetic Robots for Gastrointestinal Examination and Treatment

Magnetic actuation technology(MAT)provides novel diagnostic tools for the early screening and treatment of digestive cancers,which have high morbidity and mortality rates worldwide.The application of magnetic actuation systems and magnetic robots in gastrointestinal(GI)diagnosis and treatment to provide a comprehensive reference manual for scholars in the field of MAT research are reviewed.It describes the basic principles of magnetic actuation and magnetic field safety,introduces the design,manufacturing,control,and performance parameters of magnetic actuation systems,as well as the applicability and limitations of each system for different parts of the GI tract.It analyzes the characteristics and advantages of different types and functions of magnetic robots,summarizes the challenges faced by MAT in clinical applications,and provides an outlook on the future prospects of the field.