Výsledky vyhľadávania - "Tahmasbi, Marziyeh"

Correction to: Longitudinal quality control analysis of PET/CT systems: analyzing system stability, image quality, and the performance of silicon photomultipliers (SiPMs).

Autori: Kafhali, Morad El Tahmasbi, Marziyeh Baghous, Nor El Houda a ďalší

Zdroj: Health & Technology; Jul2025, Vol. 15 Issue 4, p823-827, 5p

Longitudinal quality control analysis of PET/CT Systems: analyzing system stability, image quality, and the performance of silicon photomultipliers (SiPMs).

Autori: Kafhali, Morad El Tahmasbi, Marziyeh Baghous, Nor El Houda a ďalší

Zdroj: Health & Technology; Jul2025, Vol. 15 Issue 4, p703-715, 13p

Diffusion Tensor Imaging Along the Perivascular Space Is a Promising Imaging Method in Parkinson's Disease: A Systematic Review and Meta‐Analysis Study.

Autori: Shirbandi, Kiarash Jafari, Mostafa Mazaheri, Fatemeh a ďalší

Zdroj: CNS Neuroscience & Therapeutics; May2025, Vol. 31 Issue 5, p1-11, 11p

Predmety: PARKINSON'S disease, DIFFUSION tensor imaging, BIOMARKERS, COGNITION disorders, CEREBROSPINAL fluid, EXTRACELLULAR fluid

Evaluating machine learning models for post-surgery treatment response assessment in glioblastoma multiforme: a comparative study of gray level co-occurrence matrix (GLCM), curvelet, and combined radiomics features selected by multiple algorithms.

Autori: Alibabaei, Sanaz Yousefipour, Mohammad Rahmani, Masoumeh a ďalší

Zdroj: BMC Medical Imaging; 9/1/2025, Vol. 25 Issue 1, p1-17, 17p

Predmety: GLIOBLASTOMA multiforme, RADIOMICS, TREATMENT effectiveness, MACHINE learning, MAGNETIC resonance imaging

Hybrid Radiomics and Machine Learning for Brain Tumors Multi‐Task Classification: An Exploratory Study on Integrating GLCM and Curvelet‐Based Features for Enhanced Accuracy.

Autori: Jafari, Mostafa Rahmani, Masoumeh Alibabaie, Sanaz a ďalší

Zdroj: Health Science Reports; Aug2025, Vol. 8 Issue 8, p1-17, 17p

Predmety: BRAIN tumors, MACHINE learning, RADIOMICS, CLASSIFICATION algorithms, MAGNETIC resonance imaging, TEST validity, TEXTURE analysis (Image processing)

Effects and Efficiency of HIFU on Treatment of Cancer and Biological Abnormalities.

Autori: Farzanegan, Zahra Tahmasbi, Marziyeh

Zdroj: Frontiers in Biomedical Technologies; 2025 Supplement, Vol. 12, p1-1, 1p

Predmety: TUMOR growth, VIRUS diseases, BLOOD-brain barrier, TISSUES, BLOOD flow

Assessing Glioblastoma Treatment Response Using Machine Learning Approach Based on Magnetic Resonance Images Radiomics: An Exploratory Study.

Autori: Sadeghinasab, Amirreza Fatahiasl, Jafar Tahmasbi, Marziyeh a ďalší

Zdroj: Health Science Reports; Jan2025, Vol. 8 Issue 1, p1-11, 11p

Predmety: MACHINE learning, RECEIVER operating characteristic curves, MAGNETIC resonance imaging, GLIOBLASTOMA multiforme, RADIOMICS

Unveiling water legacy: an interdisciplinary exploration for comprehending Siraf's historical water landscape.

Autori: Tahmasbi, Marziyeh Haghighat Bin, Mehdi Nijhuis, Steffen

Zdroj: Landscape Research; Jan2025, Vol. 50 Issue 1, p23-38, 16p

Predmety: SUSTAINABILITY, TECHNICAL reports, WATER management, DYNAMICAL systems, GEOLOGY, CULTURAL landscapes

Stereotactic Body Radiation Therapy for Lung Cancer Treatment: A Systematic Review.

Autori: Kazemi, Rahele Tahmasbi, Marziyeh

Zdroj: Reports of Radiotherapy & Oncology; 2025 Supplement, Vol. 11, p22-23, 2p

Predmety: LUNG cancer, STEREOTACTIC radiotherapy, METASTASIS, SAFETY, PATIENT selection, TREATMENT effectiveness

Pelvic radiation dose measurement for trauma patients in multifield radiographic examinations: A phantom‐based TLD dosimetry study.

Autori: Peiro, Ameneh Chegeni, Nahid Danyaei, Amir a ďalší

Zdroj: Health Science Reports; Jul2023, Vol. 6 Issue 7, p1-8, 8p

Enhancing treatment precision through radiobiological modeling for evaluating complex VMAT plans in prostate and head-and-neck cancers.

Autori: EL Kafhali, Morad Khalis, Mohammed Tahmasbi, Marziyeh a ďalší

Zdroj: Health & Technology; Nov2024, Vol. 14 Issue 6, p1175-1186, 12p

Survival Rate Prediction in Glioblastoma Patients Using Radiomics Extracted from Post-Contrast Magnetic Resonance Images: Comparison of Multiple Machine Learning Models.

Autori: Sadeghinasab, Amirreza Jafari, Mostafa Tahmasbi, Marziyeh a ďalší

Zdroj: Reports of Radiotherapy & Oncology; 2024 Supplement, Vol. 10, p52-53, 2p

Predmety: MACHINE learning, MAGNETIC resonance imaging, IMAGE analysis, BRAIN tumors, OVERALL survival

The Upright Radiotherapy Technique Versus the Conventional Supine Method for Lung Cancer Treatment and Imaging: A Systematic Review.

Autori: Mohammadpour, Mohammad Reza Tahmasbi, Marziyeh

Zdroj: Reports of Radiotherapy & Oncology; 2025 Supplement, Vol. 11, p21-21, 1/2p

Predmety: LUNG cancer, RADIOTHERAPY, PATIENT satisfaction, SUPINE position, TREATMENT effectiveness, DIAGNOSTIC imaging

Evaluating the attitudes of radiologic technology students and graduates toward their study major and career prospects: A cross‐sectional study.

Autori: Mazaheri, Fatemeh Tahmasbi, Marziyeh

Zdroj: Health Science Reports; Jun2024, Vol. 7 Issue 6, p1-10, 10p

Predmety: RADIOLOGIC technology, ATTITUDES toward technology, STUDENT attitudes, GRADUATE education, DENTAL students, INTERPROFESSIONAL education, EDUCATORS

Diagnostic test accuracy of machine learning algorithms for the detection intracranial hemorrhage: a systematic review and meta-analysis study.

Autori: Maghami, Masoud Sattari, Shahab Aldin Tahmasbi, Marziyeh a ďalší

Zdroj: BioMedical Engineering OnLine; 12/4/2023, Vol. 22 Issue 1, p1-23, 23p

Predmety: INTRACRANIAL hemorrhage, MACHINE learning, DIAGNOSIS, RECEIVER operating characteristic curves

Evaluating the gray level co-occurrence matrix-based texture features of magnetic resonance images for glioblastoma multiform patients' treatment response assessment.

Autori: Alibabaei, Sanaz Rahmani, Masoumeh Tahmasbi, Marziyeh a ďalší

Zdroj: Journal of Medical Signals & Sensors; Oct-Dec2023, Vol. 13 Issue 4, p261-271, 11p

Predmety: MAGNETIC resonance imaging, GLIOBLASTOMA multiforme, MAGNETIC resonance

Evaluating the effects of variation in CT scanning parameters on the image quality and Hounsfield units for optimization of dose in radiotherapy treatment planning: A semi‑anthropomorphic thorax phantom study.

Autori: Sorooshfard, Elahe Tahmasbi, Marziyeh Chegeni, Nahid a ďalší

Zdroj: Journal of Cancer Research & Therapeutics; Mar2023, Vol. 19 Issue 2, p426-434, 9p

Predmety: RADIOTHERAPY treatment planning, COMPUTED tomography, SIGNAL-to-noise ratio, RELIABILITY in engineering, EARLY detection of cancer

Introduction of a simple algorithm to create synthetic-Computed tomography of the head from magnetic resonance imaging.

Autori: Chegeni, Nahid Birgani, Mohamad Birgani, Fariba a ďalší

Zdroj: Journal of Medical Signals & Sensors; 2019, Vol. 9 Issue 2, p123-129, 7p

Predmety: MAGNETIC resonance imaging, MAGNETIC recording heads, BRAIN tumors, GLIOBLASTOMA multiforme, TOMOGRAPHY, BONE densitometry

Follow‐up the severity of abnormalities diagnosed in chest CT imaging of COVID‐19 patients: A cross‐sectional study.

Autori: Honarmandpour, Fatemeh Jahangirimehr, Azam Tahmasbi, Marziyeh a ďalší

Zdroj: Health Science Reports; Sep2022, Vol. 5 Issue 5, p1-10, 10p

Predmety: COMPUTED tomography, COVID-19, LUNG diseases, CROSS-sectional method, PATIENTS

Artificial Intelligence Techniques to Predict Breast Cancer Recurrence Risk: A Systematic Review.

Autori: Kazemi, Rahele Mohammadpour, Mohammad Reza Tahmasbi, Marziyeh

Zdroj: Reports of Radiotherapy & Oncology; 2025 Supplement, Vol. 11, p23-23, 1/2p

Predmety: BREAST cancer, ARTIFICIAL intelligence, MACHINE learning, DEEP learning, CANCER relapse, PREDICTIVE validity, SUPPORT vector machines, TREATMENT effectiveness