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Targeted phase-change contrast agents (PCCAs) have shown great potential for both cancer imaging and therapy. However the acoustic response of targeted PCCAs exposed to ultrasound high frame rate imaging pulses after vaporization has not been fully explored. We herein report the investigation of the change in acoustic signal of folate receptor targeted (FR)-and non-targeted (NT)-PCCAs exposed to breast...
The ability to visualize breast lesion vascularity and quantify the vascular heterogeneity using contrast-enhanced 3-D nonlinear ultrasound imaging was investigated in a clinical population. Patients (n = 236) identified with breast lesions on mammography were scanned using power Doppler imaging, contrast-enhanced 3D HI, and 3D SHI on a modified Logiq 9 scanner (GE Healthcare). Time-intensity curve...
In this study, it is A web-based image processing software which has been introduced to process Immunohistochemical images obtaining in experimentally induced diabetic rats and rank the severity of diabetes between the groups. With the software, specialist physicians can upload Images obtaining in rat groups to the system via web on own account, obtain average color intensity and intensity graphs...
In this paper, we propose a Wavelet Neural Network (WNN) classifier for breast cancer. WNN is a new kind of artificial neural network which is coming more popular these days. This method is based on the Wavelet Transform (WT) and classical neural networks. This paper explains how WNN classifies and uses formulas. The results of the experiments made to obtain the best results and the parameters affecting...
Synthesis of the p-tert-butylcalixarene compound with the amino group was carried out as given in Figure 1. The structure of the calixarene compound with the amino group was elucidated by 1H-NMR, FT-IR. After the synthesized compound was prepared in a suitable solvent medium, the nanofibers were withdrawn by electrospinning. The characterization of the nanofibers was performed by SEM.
An estimation of a resected cancer lodge localization after breast tumor surgery is a challenging task during radiotherapy planning. Knowledge about the tumor lodge position and shape could improve the radiation dose distribution. However, the tumor no longer exists after the surgery, but information about its position is available in the 3D image acquired before the surgery. Therefore, image registration...
Extreme Learning Machine (ELM) is a neural network architecture with Single Layer Feed-forward Neural Network (SLFN). For meaningful results, the structure of ELM has to be optimized through the inclusion of regularization and the ℓ2 — norm based regularization is mostly used. ℓ2-norm based regularization achieves better performance than the traditional ELM. The estimate of the regularization parameter...
Calixarenes are good carriers for cations, anions and neutral molecules because they are cyclic, can be easily derivatized, and can create molecular sizes of different sizes. Due to these properties, they have a very wide application area [1]. The use of calixarenes obtained by functioning with different functional groups in the transport and release of drugs takes place in the literature. In this...
Classification of benign and malignant masses in mammograms is one of the most difficult tasks in development of mammographic computer-aided diagnosis (CAD) system. This paper presents a deep learning-based method that utilizes a deep convolutional neural network (DCNN) to classify mammographic masses into two classes: benign and malignant masses. In order to train the DCNN for mass classification,...
This paper presents a method for classification of normal and abnormal tissues in mammograms using a deep learning approach. VGG-16 CNN deep learning architecture with convolutional filter of (3×3) is implemented on mammograms ROIs from the IRMA dataset. The deep feature matrix is computed from first fully connected layer. The results are evaluated using 10 fold cross validation on SVM, binary trees,...
Breast cancer leads the list of cancer that act on women worldwide. It starts when cells in the breast begin to build up beyond control. These cells normally create a tumour that can usually be seen on an x-ray or felt as a lump. Analysing and grading the tumour will take up much of a pathologist time. Pathologists have been largely diagnosing disease the same way for the past years, by manually reviewing...
No Evidence of Disease (NED) is breast cancer patient condition status which it indicates that they can life, no find the cancer by tested, and without any symptoms of cancer in period of times, after they received primary treatment. NED is a critical status, because it involves the treatment type and patient cancer condition factors. This paper examines about breast cancer problem in data mining...
We present an investigation related with the use of sialic acid as an auxiliary indicator for the early detection of diseases by using Terahertz Frequency-Domain Spectroscopy (THz-FDS) Technique. We propose the characterization of thin films of N-Acetylneuraminic acid-synthetic, >95% and add in colloidal solution nanoparticles of Ag (Ag-NPs) and Au (Au-NPs) in order to increase the superficial...
Terahertz (THz) imaging and tomography are modern imaging techniques allowing 2D and 3D inspection of objects over a broadband frequency range. However, the transfer of this technique to medical applications is limited to surface or subsurface inspection due to the large concentration of water molecules which are an intrinsic characteristic of biological tissues. Then, we report the results of investigations...
We demonstrate a novel approach to the problem of express diagnostics based on THz spectral features of the breast cancer and THz emission and detection provided by the topological edge channels of silicon nanosandwich-structures.
This paper presents utilization of pulsed terahertz imaging to detect and assess the margins of excised human breast tumors. The freshly excised bulk tissue and the block of the same tissue fixed in formalin and embedded in paraffin (FFPE) are scanned using the reflection imaging module. The results show that while the THz images of block tissue demonstrate strong contrast between cancerous and fibroglandular...
Long-term adjuvant endocrine therapy patients often fail to follow-up with their care providers for the recommended duration of time. We used electronic health record data, tumor registry records, and appointment logs to predict follow-up for an adjuvant endocrine therapy patient cohort. Learning predictors for follow-up may facilitate interventions that improve follow-up rates, and ultimately improve...
We propose a new mathematical growth model of primary tumor and primary metastases which may help to improve predicting accuracy of breast cancer process using an original mathematical model referred to CoM-IV and corresponding software. The CoM-IV model and predictive software: a) detect different growth periods of primary tumor and primary metastases; b) make forecast of patient survival; c) have...
Electronic health records (EHRs) represent an underused data source that has great research and clinical potential. Our goal was to quantify the value of EHRs in breast cancer risk prediction. We conducted a retrospective case-control study, gathering patients' ICD-9 diagnosis codes from an existing EHR data repository. Based on the hierarchical structure of ICD-9 codes, which are composed of 3-5...
This work utilizes xenograft murine breast cancer tumors to develop terahertz imaging methodology for freshly excised breast cancer tissue. Tumors are grown via cell injection into mice on a high-fat diet and excised for subsequent terahertz imaging. Following imaging of both freshly excised tumor bulk and interior cross-sections, the tumors are then subjected to histopathology processing for correlation...
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