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16+ results
Field: Radiology

Standardized interpretation of paediatric chest radiographs for the diagnosis of pneumonia in epidemiological studies.

Verified

Thomas Cherian, Kim Mulholland, John B. Carlin, H Ostensen et al.

Journal: PubMedYear: 2005
Citations: 649

BACKGROUND: Although radiological pneumonia is used as an outcome measure in epidemiological studies, there is considerable variability in the interpretation of chest radiographs. A standardized method for identifying radiological pneumonia would facilitate comparison of the results of vaccine trial...

Health SciencesMedicineEpidemiologyOpen Access
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CoroDet: A deep learning based classification for COVID-19 detection using chest X-ray images

Verified

Emtiaz Hussain, Mahmudul Hasan, Anisur Rahman, Ickjai Lee et al.

Journal: Chaos Solitons & FractalsYear: 2020Citations: 454

Highlights • A 22-layer CNN architecture, which has achieved an accuracy of 99.1% for 2 class classification, 94.2% for 3 class classification, and 91.2% for 4 class classification. To the best of our knowledge, the accuracy of our proposed CoroDet method is higher than the state-of-the-art method f...

Health SciencesMedicineRadiology, Nuclear Medicine and ImagingOpen Access
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Application of deep learning in detecting neurological disorders from magnetic resonance images: a survey on the detection of Alzheimer’s disease, Parkinson’s disease and schizophrenia

Verified

Manan Binth Taj Noor, Nusrat Zerin Zenia, M. Shamim Kaiser, Shamim Al Mamun et al.

Journal: Brain InformaticsYear: 2020Citations: 335

Neuroimaging, in particular magnetic resonance imaging (MRI), has been playing an important role in understanding brain functionalities and its disorders during the last couple of decades. These cutting-edge MRI scans, supported by high-performance computational tools and novel ML techniques, have o...

Life SciencesNeuroscienceNeurologyOpen Access
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Diffusion-weighted MR imaging of intracerebral masses: comparison with conventional MR imaging and histologic findings.

Verified

Tadeusz Stadnik, C. Chaskis, Alex Michotte, Wael Shabana et al.

Journal: PubMedYear: 2001Citations: 334

BACKGROUND AND PURPOSE: The purposes of this study were to find the role of diffusion-weighted MR imaging in characterizing intracerebral masses and to find a correlation, if any, between the different parameters of diffusion-weighted imaging and histologic analysis of tumors. The usefulness of diff...

Health SciencesMedicineGeneticsOpen Access
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Topologically Convergent and Divergent Structural Connectivity Patterns between Patients with Remitted Geriatric Depression and Amnestic Mild Cognitive Impairment

Verified

Feng Bai, Ni Shu, Yonggui Yuan, Yongmei Shi et al.

Journal: Journal of NeuroscienceYear: 2012Citations: 306

Alzheimer's disease (AD) can be conceptualized as a disconnection syndrome. Both remitted geriatric depression (RGD) and amnestic mild cognitive impairment (aMCI) are associated with a high risk for developing AD. However, little is known about the similarities and differences in the topological pat...

Life SciencesNeuroscienceCognitive NeuroscienceOpen Access
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Quantitation of Emphysema by Computed Tomography Using a “Density Mask” Program and Correlation with Pulmonary Function Tests

Verified

Mario Kinsella, Néstor L. Müller, Raja T. Abboud, Nancy Morrison et al.

Journal: CHEST JournalYear: 1990Citations: 302

We used a CT program "density mask" outlining areas with attenuation values less than -910 HU, to indicate areas of emphysema on a chest CT and to provide an overall percentage of lung involvement by emphysema. The "density mask" quantitation of emphysema was previously shown to correlate well with ...

Health SciencesMedicinePulmonary and Respiratory Medicine
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Synthetic MRI for Clinical Neuroimaging: Results of the Magnetic Resonance Image Compilation (MAGiC) Prospective, Multicenter, Multireader Trial

Verified

Lawrence Tanenbaum, Apostolos John Tsiouris, Angela N. Johnson, Thomas P. Naidich et al.

Journal: American Journal of NeuroradiologyYear: 2017Citations: 285

BACKGROUND AND PURPOSE: Synthetic MR imaging enables reconstruction of various image contrasts from 1 scan, reducing scan times and potentially providing novel information. This study is the first large, prospective comparison of synthetic-versus-conventional MR imaging for routine neuroimaging. MAT...

Health SciencesMedicineRadiology, Nuclear Medicine and ImagingOpen Access
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Vision transformer and explainable transfer learning models for auto detection of kidney cyst, stone and tumor from CT-radiography

Verified

Md Nazmul Islam, Mehedi Hasan, Md Kabir Hossain, Md. Golam Rabiul Alam et al.

Journal: Scientific ReportsYear: 2022Citations: 276

Renal failure, a public health concern, and the scarcity of nephrologists around the globe have necessitated the development of an AI-based system to auto-diagnose kidney diseases. This research deals with the three major renal diseases categories: kidney stones, cysts, and tumors, and gathered and ...

Physical SciencesEngineeringBiomedical EngineeringOpen Access
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Tuberculosis detection from chest x-rays for triaging in a high tuberculosis-burden setting: an evaluation of five artificial intelligence algorithms

Verified

Zhi Zhen Qin, Shahriar Ahmed, Mohammad Shahnewaz Sarker, Kishor Kumar Paul et al.

Journal: The Lancet Digital HealthYear: 2021Citations: 271

BACKGROUND: Artificial intelligence (AI) algorithms can be trained to recognise tuberculosis-related abnormalities on chest radiographs. Various AI algorithms are available commercially, yet there is little impartial evidence on how their performance compares with each other and with radiologists. W...

Health SciencesMedicineRadiology, Nuclear Medicine and ImagingOpen Access
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VGG-SCNet: A VGG Net-Based Deep Learning Framework for Brain Tumor Detection on MRI Images

Verified

Mohammad Shahjahan Majib, Md. Mahbubur Rahman, T. M. Shahriar Sazzad, Nafiz Imtiaz Khan et al.

Journal: IEEE AccessYear: 2021Citations: 260

A brain tumor is a life-threatening neurological condition caused by the unregulated development of cells inside the brain or skull. The death rate of people with this condition is steadily increasing. Early diagnosis of malignant tumors is critical for providing treatment to patients, and early dis...

Life SciencesNeuroscienceNeurologyOpen Access
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Magnetic resonance imaging in individuals with cardiovascular implantable electronic devices

Verified

Ariel Roguin, Juerg Schwitter, Christian Vahlhaus, Massimo Lombardi et al.

Journal: EP EuropaceYear: 2008Citations: 255

Magnetic resonance (MR) imaging has unparalleled soft-tissue imaging capabilities. The presence of devices such as pacemakers and implantable cardioverter-defibrillators (ICDs), however, was historically considered a contraindication to MR imaging. We summarize the potential hazards of the device-MR...

Health SciencesMedicineRadiology, Nuclear Medicine and ImagingOpen Access
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Robust clinical applicable CNN and U-Net based algorithm for MRI classification and segmentation for brain tumor

Verified

Atika Akter, Nazeela Nosheen, Sabbir Ahmed, Mariom Hossain et al.

Journal: Expert Systems with ApplicationsYear: 2023Citations: 242

Early diagnosis of brain tumors is critical for enhancing patient prognosis and treatment options, while accurate classification and segmentation of brain tumors are vital for developing personalized treatment strategies. Despite the widespread use of Magnetic Resonance Imaging (MRI) for brain exami...

Life SciencesNeuroscienceNeurologyOpen Access
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A Review of the Effectiveness of Neuroimaging Modalities for the Detection of Traumatic Brain Injury

Verified

Franck Amyot, David B. Arciniegas, Michael P. Brazaitis, Kenneth C. Curley et al.

Journal: Journal of NeurotraumaYear: 2015Citations: 233

The incidence of traumatic brain injury (TBI) in the United States was 3.5 million cases in 2009, according to the Centers for Disease Control and Prevention. It is a contributing factor in 30.5% of injury-related deaths among civilians. Additionally, since 2000, more than 260,000 service members we...

Health SciencesMedicineNeurology
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Vision Transformers, Ensemble Model, and Transfer Learning Leveraging Explainable AI for Brain Tumor Detection and Classification

Verified

Shahriar Hossain, Amitabha Chakrabarty, Thippa Reddy Gadekallu, Mamoun Alazab et al.

Journal: IEEE Journal of Biomedical and Health InformaticsYear: 2023Citations: 206

The abnormal growth of malignant or nonmalignant tissues in the brain causes long-term damage to the brain. Magnetic resonance imaging (MRI) is one of the most common methods of detecting brain tumors. To determine whether a patient has a brain tumor, MRI filters are physically examined by experts a...

Life SciencesNeuroscienceNeurology
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Uterine Leiomyoma: Available Medical Treatments and New Possible Therapeutic Options

Verified

Md Soriful Islam, Olga Protic, Stefano Raffaele Giannubilo, Paolo Toti et al.

Journal: The Journal of Clinical Endocrinology & MetabolismYear: 2013Citations: 204

CONTEXT: Uterine leiomyomas (fibroids or myomas) are benign tumors of the uterus and are clinically apparent in up to 25% of reproductive-age women. Heavy or abnormal uterine bleeding, pelvic pain or pressure, infertility, and recurrent pregnancy loss are generally associated with leiomyoma. Althoug...

Health SciencesMedicineObstetrics and GynecologyOpen Access
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