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- 实验方案
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[IEEE 2018 IEEE Biomedical Circuits and Systems Conference (BioCAS) - Cleveland, OH, USA (2018.10.17-2018.10.19)] 2018 IEEE Biomedical Circuits and Systems Conference (BioCAS) - Gaussian Monocycle Pulse Generator with Calibration Circuit for Breast Cancer Detection
摘要： Gaussian Monocycle Pulses (GMP) play a very important role in a radar-based painless breast cancer detection system. In order to guarantee the detection accuracy, it is necessary to stabilize the pulse width and the amplitude under the influence of the manufacturing variation of MOSFETs. Therefore, in this paper, the GMP generator with a calibration circuit is proposed. The calibration circuit for adjusting the delay time of each path is realized by MOS capacitor array. The proposed GMP generator has a center frequency of 5.5 GHz, -3dB bandwidth from 2.8 GHz to 9.1 GHz, and 498.6 μW power consumption.
关键词： Gaussian Monocycle Pulse (GMP),equivalent time sampling,breast cancer detection system,calibration circuit
更新于2025-09-23 15:23:52
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[IEEE 2017 IEEE 17th International Conference on Bioinformatics and Bioengineering (BIBE) - Washington, DC (2017.10.23-2017.10.25)] 2017 IEEE 17th International Conference on Bioinformatics and Bioengineering (BIBE) - A novel low-complexity framework in ultra-wideband imaging for breast cancer detection
摘要： In this research work, a novel framework is proposed as an efficient successor to traditional imaging methods for breast cancer detection in order to decrease the computational complexity. In this framework, the breast is divided into segments in an iterative process and in each iteration, the one having the most probability of containing tumor with lowest possible resolution is selected by using suitable decision metrics. After finding the smallest tumor-containing segment, the resolution is increased in the detected tumor-containing segment, leaving the other parts of the breast image with low resolution. Our framework is applied on the most common used beamforming techniques, such as delay and sum (DAS) and delay multiply and sum (DMAS) and according to simulation results, our framework can decrease the computational complexity significantly for both DAS and DMAS without imposing any degradation on accuracy of basic algorithms. The amount of complexity reduction can be determined manually or automatically based on two proposed methods that are described in this framework.
关键词： breast cancer detection,low complexity computational methods,DAS,DMAS,Microwave imaging
更新于2025-09-23 15:21:21
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Technology, application and potential of dynamic breast thermography for the detection of breast cancer
摘要： Early breast cancer detection improves the chances of survival, increases the options for curative treatment and helps reduce costs. There are a variety of screening techniques available to detect breast cancer such as mammography, magnetic resonance imaging and ultrasound. However, their sensitivities and specificities are suboptimal, especially in breasts with dense tissue. Infrared breast thermography is an adjunct screening technique that has been associated with the detection of early signs of breast cancer. However, its success has been limited. Dynamic infrared thermography was introduced to improve the detection of breast cancer and reduce the false positive and false negative rates. This works reviews the different modalities of dynamic infrared thermography, their advantages, shortcomings and opportunities for future development. This paper also covers recent advances, suggestions and possible directions for future work in the fields of numerical simulations, automatic feature identification and artificial intelligence for improving the detection of breast cancer using dynamic infrared thermography.
关键词： Dynamic thermography,Breast cancer detection,Cold challenge
更新于2025-09-23 15:21:21
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New Perspectives in Breast Imaging || Near-Field Radar Microwave Imaging as an Add-on Modality to Mammography
摘要： According to global statistics, there is a high incidence of cancer in western countries; and, due to the limited resources available in most healthcare systems, it seems like one of the most feasible options to fight against cancer might be strict prevention policies—such as eliminating carcinogens in people’s daily lives. Nevertheless, early cancer detection and effective treatment are still necessary, and understanding their efficacy and limitations are important issues that need to be addressed in order to ultimately enhance patients’ survival rate. In the case of breast cancer, some of the problems faced by conventional mammography have been addressed in the literature; they include high rate of false-positive and false-negative results, as well as the possibility of overdiagnosis. New technologies, such as digital breast tomosynthesis (DBT), have been able to improve the sensitivity and specificity by using 3D imaging. However, the low contrast (1%) existing between tumors and healthy fibroglandular tissue at X-ray frequencies has been identified as one of the main causes of misdiagnosis in both conventional 2D mammography and DBT. Near-field radar imaging (NRI) provides a unique opportunity to overcome this problem, since the contrast existing between the aforementioned tissues is intrinsically higher (10%) at microwave frequencies. Moreover, the low resolution and highly complex scattering patterns of microwave systems can be enhanced by using prior information from other modalities, such as the DBT. Therefore, a multimodal DBT/NRI imaging system is proposed to exploit their individual strengths while minimizing their weaknesses. In this work, the foundation of this idea is reviewed, and a preliminary design and experimental validation of the NRI system, used as a DBT complement, is introduced.
关键词： breast cancer statistics,digital breast tomosynthesis,microwave imaging,antipodal Vivaldi antennas,near-field radar imaging,breast cancer detection
更新于2025-09-23 15:21:01
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[IEEE 2019 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC) - Munich, Germany (2019.6.23-2019.6.27)] 2019 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC) - Probing Neuronal Activity using Membrane Interfacial Water
摘要： The use of high-volume quantitative radiomics features extracted from multi-parametric magnetic resonance imaging (MP-MRI) is gaining attraction for the autodetection of prostate tumors, since it provides a plethora of mineable data, which can be used for both detection and prognosis of prostate cancer. While current voxel-resolution radiomics-driven prostate tumor detection approaches utilize quantitative radiomics features associated with individual voxels on an independent basis, the incorporation of additional information regarding the spatial and radiomics feature relationships between voxels has significant potential for achieving a more reliable detection performance. Motivated by this, we present a novel approach for automatic prostate cancer detection using a radiomics-driven conditional random field (RD-CRF) framework. In addition to the high-throughput extraction and utilization of a comprehensive set of voxel-level quantitative radiomics features, the proposed RD-CRF framework leverages inter-voxel spatial and radiomics feature relationships to ensure that the autodetected tumor candidates exhibit interconnected tissue characteristics reflective of cancerous tumors. We evaluated the performance of the proposed framework using clinical prostate MP-MRI data of 20 patients, and the results of RD-CRF framework demonstrated a clear improvement with respect to the state-of-the-art in quantitative radiomics for automatic voxel-resolution prostate cancer detection.
关键词： multi-parametric magnetic resonance imaging (MP-MRI),Automatic prostate cancer detection,radiomics,feature model,conditional random fields (CRF)
更新于2025-09-23 15:21:01
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Introducing New Conjugated Quantum Dots for Photothermal Therapy in Biological Applications
摘要： It is well-known that near-infrared (NIR) light sources are appropriate to ablate benign tumor irreversibly using heat treatment even in deep tissues. The laser light penetration into the skin in these wavelengths is deep (3–5 mm). Applying new stable materials for emitting NIR wavelengths in tumor positions can help cancer treatment. In this paper, synthesis of the conjugated core-multishell Ag/SiO2/Ag and Au/SiO2/Au quantum dots (QDs) with indocyanine green (ICG) is done and their theoretical and experimental absorptions and emissions in the NIR region are investigated. Thus, heat generation (high-resolution medical imaging capabilities) and emission enhancement are explained and described based on the FRET model for the proposed core-multishell QDs and it is shown that Ag/SiO2/Ag with ICG presents 4 times higher emission rate versus ICG alone in NIR region. Also, because of the plasmon hybridization and also resonance light penetration enhancement, the temperature in tissues increases that is useful for photothermal therapy and NIR high-resolution medical imaging for deep tissues. As an alternative application, these nanoparticles with amazing features are used as a heat source in cancer treatment for shallow and deep tissues. Finally, it is shown that Ag/SiO2/Ag QDs are the best solution for this purpose.
关键词： Cancer detection,FRET,Imaging,Quantum dots,Photothermal therapy
更新于2025-09-23 15:21:01
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Parallel K-Means Clustering for Brain Cancer Detection Using Hyperspectral Images
摘要： The precise delineation of brain cancer is a crucial task during surgery. There are several techniques employed during surgical procedures to guide neurosurgeons in the tumor resection. However, hyperspectral imaging (HSI) is a promising non-invasive and non-ionizing imaging technique that could improve and complement the currently used methods. The HypErspectraL Imaging Cancer Detection (HELICoiD) European project has addressed the development of a methodology for tumor tissue detection and delineation exploiting HSI techniques. In this approach, the K-means algorithm emerged in the delimitation of tumor borders, which is of crucial importance. The main drawback is the computational complexity of this algorithm. This paper describes the development of the K-means clustering algorithm on different parallel architectures, in order to provide real-time processing during surgical procedures. This algorithm will generate an unsupervised segmentation map that, combined with a supervised classification map, will offer guidance to the neurosurgeon during the tumor resection task. We present parallel K-means clustering based on OpenMP, CUDA and OpenCL paradigms. These algorithms have been validated through an in-vivo hyperspectral human brain image database. Experimental results show that the CUDA version can achieve a speed-up of ~150× with respect to a sequential processing. The remarkable result obtained in this paper makes possible the development of a real-time classification system.
关键词： unsupervised clustering,brain cancer detection,Graphics Processing Units (GPUs),OpenCL,CUDA,K-means,OpenMP,hyperspectral imaging
更新于2025-09-23 15:21:01
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Advances and perspectives in neara??infrared fluorescent organic probes for surgical oncology
摘要： Surgical resection of solid tumors is currently the most efficient and preferred therapeutic strategy for treating cancer. Despite significant medical, technical, and scientific advances, the complete treatment of this lethal disease is still a challenging task. New imaging techniques and contrast agents are urgently needed to improve cytoreductive surgery and patient outcomes. Tumor-targeted probes are valuable for guiding a surgical resection of tumor from subjective judgments to visual inspection. Near-infrared (NIR) fluorescent imaging is a promising technology in preclinical and clinical tumor diagnosis and therapy. The rapid development in NIR fluorophores with improved optical properties, targeting strategies, and imaging devices has brought about prospective study of novel NIR nanomaterials for intraoperative tumor detection. In this review, we summarize the recent development in NIR-emitting organic fluorophores and cancer-targeting strategies that specifically target and accumulate in tumors for the molecular imaging of cancerous cells. We believe this technique utilizing new fluorescent probes with an intraoperative optical imaging capacity could provide a more sensitive and accurate method for cancer resection guidance, thereby resulting in better surgical outcomes.
关键词： cancer detection,intraoperative optical imaging,near-infrared fluorescent probes,surgical resection
更新于2025-09-23 15:19:57
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Metasurfaces for Advanced Sensing and Diagnostics
摘要： Interest in sensors and their applications is rapidly evolving, mainly driven by the huge demand of technologies whose ultimate purpose is to improve and enhance health and safety. Different electromagnetic technologies have been recently used and achieved good performances. Despite the plethora of literature, limitations are still present: limited response control, narrow bandwidth, and large dimensions. MetaSurfaces, artificial 2D materials with peculiar electromagnetic properties, can help to overcome such issues. In this paper, a generic tool to model, design, and manufacture MetaSurface sensors is developed. First, their properties are evaluated in terms of impedance and constitutive parameters. Then, they are linked to the structure physical dimensions. Finally, the proposed method is applied to realize devices for advanced sensing and medical diagnostic applications: glucose measurements, cancer stage detection, water content recognition, and blood oxygen level analysis. The proposed method paves a new way to realize sensors and control their properties at will. Most importantly, it has great potential to be used for many other practical applications, beyond sensing and diagnostics.
关键词： MetaSurface,sensors,cancer detection,modeling,medical diagnostics,glucose measurements,design
更新于2025-09-19 17:15:36
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Early gastric cancer detection in high-risk patients: a multicentre randomised controlled trial on the effect of second-generation narrow band imaging
摘要： Objective early detection of gastric cancer has been the topic of major efforts in high prevalence areas. Whether advanced imaging methods, such as second-generation narrow band imaging (2g- nBi) can improve early detection, is unknown. Design This open-label, randomised, controlled tandem trial was conducted in 13 hospitals. Patients at increased risk for gastric cancer were randomly assigned to primary white light imaging (Wli) followed by secondary 2g- nBi (Wli group: n=2258) and primary 2g- nBi followed by secondary Wli (2g- nBi group: n=2265) performed by the same examiner. suspected early gastric cancer (egc) lesions in both groups were biopsied. Primary endpoint was the rate of egc patients in the primary examination. The main secondary endpoint was the positive predictive value (PPV) for egc in suspicious lesions detected (primary examination). results egcs were found in 44 (1.9%) and 53 (2.3%; p=0.412) patients in the Wli and 2g- nBi groups, respectively, during primary egD. in a post hoc analysis, the overall rate of lesions detected at the second examination was 25% (n=36/145), with no significant differences between groups. PPV for egc in suspicious lesions was 13.5% and 20.9% in the Wli (50/371 target lesions) and 2g- nBi groups (59/282 target lesions), respectively (p=0.015). Conclusion The overall sensitivity of primary endoscopy for the detection of egc in high- risk patients was only 75% and should be improved. 2g- nBi did not increase egc detection rate over conventional Wli. The impact of a slightly better PPV of 2g- nBi has to be evaluated further.
关键词： positive predictive value,narrow band imaging,early gastric cancer,detection rate,white light imaging
更新于2025-09-19 17:13:59