Biomedical Sensing System Based on Image Analysis
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Biomedical Sensors".
Deadline for manuscript submissions: 31 July 2024 | Viewed by 199
Special Issue Editors
Interests: microscopic image and medical image analysis; artificial intelligence; pattern recognition; machine learning; machine vision; multimedia retrieval; intelligent microscopic imaging technology
Special Issues, Collections and Topics in MDPI journals
Interests: biomedical engineering; artificial intelligence; pattern recognition; machine vision; machine learning; medical sensor
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Medical images are one of the most important sources of biomedical sensing data, including radiological images, pathological images and photographs of affected areas with special instruments. The sensor system developed based on medical images can not only integrate multi-modal medical data information to realize real-time monitoring of patients' conditions, but also predict patients' prognosis and even rehabilitation. In addition, biomedical sensing systems based on medical images offer the possibility of a standardized disease assessment that removes subjective judgments. In particular, some new techniques are introduced in this domain, such as Medical Image Processing Knowledge Editing for LLM Aircraft Detection and Recognition with Few-Shot Medical Image Segmentation based on domain adaption multi-omics information integration and Infrared Small Target Detection. Finally, we welcome the submission of manuscripts to our Special Issue on (but not limited to) the following topics:
- Test and analysis of the application effect of medical image key point detection algorithms;
- Test and analysis of the application effect of medical image segmentation algorithms;
- Test and analysis of the application effect of medical image target classification algorithms;
- The application of artificial intelligence in this digital measurement of human anatomy;
- Application of artificial intelligence in the diagnosis of coronary heart disease;
- Application of artificial intelligence in the diagnosis of pulmonary nodules;
- Application of human intelligence in spinal measurement;
- Calculation of the risk of disease or other unexpected events for healthy people or patients based on medical images;
- Use of real-time medical images to detect disease in patients, so as to assist treatment or provide an early warning of changes in patients' conditions;
- Perform diagnosis and differential diagnosis through medical images during the course of the disease, assist in the formulation of medical plans and predict the prognosis of patients;
- Based on medical images, evaluate the information that is difficult to obtain manually on images, including molecular biological characteristics and metabolites;
- Adopt new methods, semi-automatic or fully automatic medical information extraction, so as to improve efficiency.
Dr. Chen Li
Prof. Dr. Marcin Grzegorzek
Guest Editors
Manuscript Submission Information
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Keywords
- medical image analysis
- image classification
- image segmentation
- object detection
- feature extraction
Planned Papers
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
Title: Non-invasive estimation of bone position and orientation for knee replacement therapy using differential EIT - a simulation study
Authors: Jakob Schrott; Christian Stadler; Christoph Hintermüller
Affiliation: Institute of Measurement Technology, Johannes Kepler University, Linz, Austria
Abstract: The advantage of electrical impedance tomography is, it does not require any ionizing radiation compared to the X-ray or CT imaging methods required by the aforementioned marker based approaches.
In this simulation study it is tested whether EIT can be used to locate the femur inside the thigh and provide and find an appropriate estimate of its axis orientation. The governing idea is to reduce wound healing disorders and avoid weak spots in the bone structure by replacing the marker based approaches by simple EIT based measurements on the thigh and lower leg.
The basic approach tested is discussed in section 2 and the results obtained through simulation and a preliminary measurement of a simple saline gel model of the thigh are presented in section 3. Section 4 discusses the obtained results, encountered issues and findings.
