ReviewMicromachines2023
Microwave Imaging and Sensing Techniques for Breast Cancer Detection.
Review in Micromachines, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed.
- Microwave breast imaging: A review of clinical potential and technological advances.World journal of methodology · 2026Review
- Microwave Metasurface-Based Sensor with Artificial Intelligence for Early Breast Tumor Detection.Micromachines · 2026Article
- Combined Use of Microwave Sensing Technologies and Artificial Intelligence for Biomedical Monitoring and Imaging.Biosensors · 2026Review
- An accurate analytical modeling method for microwave-based breast tumor detection and phantom manufacturing.Biomedical engineering letters · 2026Article
- Conformal On-Body Antenna System Integrated with Deep Learning for Non-Invasive Breast Cancer Detection.Sensors (Basel, Switzerland) · 2025Article
- A Line-Source Approach for Simulating MammoWave Microwave Imaging Apparatus for Breast Lesion Detection.Sensors (Basel, Switzerland) · 2025Article
- Nanomaterials as electromagnetic sensors for tumour detection.Nanomedicine (London, England) · 2025Article
- A Low-Cost Optomechatronic Diffuse Optical Mammography System for 3D Image Reconstruction: Proof of Concept.Diagnostics (Basel, Switzerland) · 2025Article
- Breast Cancer Detection via Multi-Tiered Self-Contrastive Learning in Microwave Radiometric Imaging.Diagnostics (Basel, Switzerland) · 2025Article
- XGBoost Enhances the Performance of SAFE: A Novel Microwave Imaging System for Early Detection of Malignant Breast Cancer.Cancers · 2025Article
- Advances in breast cancer diagnosis: a comprehensive review of imaging, biosensors, and emerging wearable technologies.Frontiers in oncology · 2025Review
- BCED-Net: Breast Cancer Ensemble Diagnosis Network using transfer learning and the XGBoost classifier with mammography images.Osong public health and research perspectives · 2024Article
- A Breast Tumor Monitoring Vest with Flexible UWB Antennas-A Proof-of-Concept Study Using Realistic Breast Phantoms.Micromachines · 2024Article
- Review of Microwave Near-Field Sensing and Imaging Devices in Medical Applications.Sensors (Basel, Switzerland) · 2024Review
- A High-Resolution 3D Ultrasound Imaging System Oriented towards a Specific Application in Breast Cancer Detection Based on a 1 × 256 Ring Array.Micromachines · 2024Article
- Elucidating the evolving role of cuproptosis in breast cancer progression.International journal of biological sciences · 2024Review
- Microwave Breast Sensing via Deep Learning for Tumor Spatial Localization by Probability Maps.Bioengineering (Basel, Switzerland) · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Medical imaging techniques, including X-ray mammography, ultrasound, and magnetic resonance imaging, play a crucial role in the timely identification and monitoring of breast cancer. However, these conventional imaging modalities have their limitations, and there is a need for a more accurate and sensitive alternative. Microwave imaging has emerged as a promising technique for breast cancer detection due to its non-ionizing, non-invasive, and cost-effective nature. Recent advancements in microwave imaging and sensing techniques have opened up new possibilities for the early diagnosis and treatment of breast cancer. By combining microwave sensing with machine learning techniques, microwave imaging approaches can rapidly and affordably identify and classify breast tumors. This manuscript provides a comprehensive overview of the latest developments in microwave imaging and sensing techniques for the early detection of breast cancer. It discusses the principles and applications of microwave imaging and highlights its advantages over conventional imaging modalities. The manuscript also delves into integrating machine learning algorithms to enhance the accuracy and efficiency of microwave imaging in breast cancer detection.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.