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Fusion of Texture and Shape-Based Statistical Features for MRI Image Retrieval System
Published in D. P. Acharjya, V. Santhi, Bio-Inspired Computing for Image and Video Processing, 2018
In past years, medical database systems only made available textual information about patients in treatment; soon after, this information was stored in huge databases where queries could be answered by searching for the text information. At the present day, there is a tremendous number of medical images being generated in hospitals, and it is expected that the quantity of such images will further increase exponentially in the time to come. The significance of new medical technologies, such as picture archiving and communication systems (PACS), ultrasound, magnetic resonance imaging (MRI), computed tomography (CT), and X-ray radiography, has resulted in a volatile growth in the number of images stored in the databases.
Introduction to medical imaging
Published in David A Lisle, Imaging for Students, 2012
Many medical imaging departments now employ large computer storage facilities and networks known as picture archiving and communication systems (PACS). Images obtained by CR and DR are stored digitally, as are images from other modalities including computed tomography (CT), magnetic resonance imaging (MRI), ultrasound (US) and scintigraphy. PACS systems allow instant recall and display of a patient’s imaging studies. Images can be displayed on monitors throughout the hospital in wards, meeting rooms and operating theatres as required.
Healthcare Data Monitoring under Internet of Things
Published in Sourav Banerjee, Chinmay Chakraborty, Kousik Dasgupta, Green Computing and Predictive Analytics for Healthcare, 2020
Chinmay Chakraborty, Sanjukta Bhattacharya
The most enabling technologies of IoT are wireless sensor networks (WSN) and cloud computing. A WSN consists of nodes, router/gateway and coordinators. The cloud computing framework gives storage resources, computing and resources on an on-demand basis. Chen et al. [18] discussed real-time online vehicle diagnostics and early fault measurement method. Telehealth, telemedicine, e-health, m-health, digital medicine, precision medicine, digital health and personalized medicine are used effectively. The telemedicine tool plays an important role in chronic wound monitoring using the m-health scenario [19]. Health 4.0 technology is performing well and handles the critical medical infrastructure. The major principles of Health 4.0 are modularity, real-time capability, virtualization, service orientation, decentralization and interoperability. The mobile IoT manages asthma disease, heart disease and diabetes and processes medical data for monitoring. This data is associated with pharmaceutical and non-pharmaceutical therapy. The smart inhaler enhances the efficiency of therapy, minimizes serious incidents, increases quality healthcare, enhances documentation and reduces hospitalization. Asthma management needs sufficient adherence to therapy, monitoring of asthma control and prevention of environmental triggers [20]. Chakraborty et al. [21] discussed the telemedicine-based wireless body area network platforms for remote health monitoring. The various types of biomedical sensors have been presented. In digital healthcare systems, the patients demand accurate diagnosis. It depends on continuous patient monitoring. The patient’s vital signs are taken by computerized devices and processed to the patient data management system (PDMS) server. The biomedical images are kept at the hospital’s central node, i.e. picture archiving and communication system (PACS) in the form of DICOM (digital images and communication in medicine) files. This file is supported by multidimensional images and provides rich meta clinical information like demographic information, parameter acquisition, operator’s identifiers, practitioners, image dimensions [22]. M-health data is processed wirelessly to IoT servers for storage, transmitting and receiving. The smart sensed data management under IoT-healthcare is the most promising nowadays [23]. The main features of m-health are as follows: (a) compact and easy-to-wear (TICKR – heart rate monitor; Fitbit Surge, Forerunner 920XT – smartwatch; iBGStar – blood sugar meter); (b) IP-enabled and wireless connectivity (the Infrared Data Association, Nike+, Bluetooth Low Energy, ANT, ZigBee, near-field communication, Wi-Fi); and (c) low power consumption [24].
IoT-based patient stretcher movement simulation in smart hospital using type-2 fuzzy sets systems
Published in Production Planning & Control, 2023
C. B. Sivaparthipan, M. Anand, Nidhi Agarwal, Mallika Dhingra, Laxmi Raja, Akila Victor, S. A. Amala Nirmal Doss
With the help of the interface design, the patient stretcher can be tracked with the help of the GPS tracking sensor. This sensor connects to the sensor attached to the stretcher. Then it forms the system to produce the information about where the bed is located and the patient details who occupied it. Here the medical images are captured, and the many types of the sensor make a full analysis of the system to produce the formation of the digital information in the communication capabilities (Kataria et al. 2021). The Digital Imaging and Communications in Medicine (DICOM) standard provides a thorough description of the information content, structure, encoding, and communications protocols for the electronic transaction of diagnostic and therapeutic images as well as image-related data. It is most frequently used to store and transmit medical images, making it possible to integrate medical imaging equipment from many manufacturers, including scanners, servers, workstations, printers, network infrastructure, and picture archiving and communication systems (PACS). This mechanism provides automatic movements of the stretcher. Between the stretcher and microcontroller, the driver circuit act as an interface. AT mega microcontroller is the heart of the system and has 54 input and output pins. It has 4 Universal asynchronous receiver-transmitter (UARTs) and 16 analogue inputs. A UART is typically an individual integrated circuit (IC) used for serial communications through a serial port on a computer or peripheral device. Microcontroller chips frequently include one or more UART peripherals. Automobiles, smart cards, and SIMs all make use of specialised UARTs. In UART, local clock references are used to detect data through baud rate generation. The sender generates a clock signal that determines the transmission rate, which the receiver also uses to detect incoming data. The receiver generates its clock signal and uses it to sample the data at regular intervals determined by the local clock. Data is transmitted as a series of bits, starting with a start bit, followed by data bits, and ending with a stop bit. The receiver samples the data at the midpoint of each data bit using the local clock reference to ensure accurate detection, even when the sender and receiver clocks are not perfectly synchronised. The sensors provide the data to the controller through the input pins and update the data to the server using the UART port. It makes the stretcher move. Here, the biometric sensor gets each patient’s information through the fingerprint. The respiration sensor is used for monitoring and gives information about the depth of breathing. The respiration sensor is a sensitive girth sensor that is attached to a length-adjustable webbing belt by an easy-fitting high durability woven elastic band. The respiration waveform is produced once the chest or abdominal expansion or contraction is recognised. The heartbeat sensor is also attached to this system. When the patient’s fingerprint is placed on the sensor, the digital output of the patient’s heartbeat is shown in the indicator.