Michael Masoomi

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Ministry of Health

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Dive into the research topics where Michael Masoomi is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

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Developing A Novel Deep Learning Technique using Convolutional Neural Network (CNN) for Automated Diagnosis and Differentiating Lung Infections on Chest X-ray.
Alkandari, L. (PI), MASOOMI, M. (CoI), SHAKER, T. (CoI), Masoomi, M. (CoI) & RAMZY, H. (CoI)
22/10/23 → …
Project: Applied Research › Applied Research 2023 Cycle 2
3D Volume Rendering Model and Pixelated Quantitative CT for Accurate Assessment of the Extent and Severity of Patients with COVID-19
Masoomi, M. (PI)
1/10/20 → 14/07/21
Project: General Research › General Research 2020 Cycle 2 (Corona)
Establishment of National DRL for CT in Hybrid Imaging Studies "The Second Phase of National NM CT (PET) Dose Audit for KW population – 2019.
Masoomi, M. (PI)
1/01/20 → 10/07/20
Project: General Research › General Research 2019 Cycle 2
Diagnostic Accuracy and Impact of F18-LDOPA With TOF PET-CT in Assessing Preoperative Management of Neonatal Hyperinsulinism, "A Non-Invasive Approach"
Masoomi, M. (PI)
1/10/19 → 1/10/21
Project: General Research › General Research 2018 Cycle 1
A Novel Voxel Based Quantitation in Identifying Scintigraphy Bone Lesions and its Potential Impact on Diagnostic and Therapeutic Applications
Masoomi, M. (PI)
1/03/19 → 30/04/20
Project: General Research › General Research 2018 Cycle 2

1 Comment/debate

Masoomi, M. A., Al-Kandari, L., & Al-Shammeri, I. (2021). Combining 3d rendering model and pixelated quantitative ct for rapid assessment of lung affected with covid-19 and need for oxygenation. BMJ Case Reports, 14(1), Article 241060. https://doi.org/10.1136/bcr-2020-241060

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1 Scopus citations

Michael Masoomi

Personal profile

External positions

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Collaborations and top research areas from the last five years

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Developing A Novel Deep Learning Technique using Convolutional Neural Network (CNN) for Automated Diagnosis and Differentiating Lung Infections on Chest X-ray.

3D Volume Rendering Model and Pixelated Quantitative CT for Accurate Assessment of the Extent and Severity of Patients with COVID-19

Establishment of National DRL for CT in Hybrid Imaging Studies "The Second Phase of National NM CT (PET) Dose Audit for KW population – 2019.

Diagnostic Accuracy and Impact of F18-LDOPA With TOF PET-CT in Assessing Preoperative Management of Neonatal Hyperinsulinism, "A Non-Invasive Approach"

A Novel Voxel Based Quantitation in Identifying Scintigraphy Bone Lesions and its Potential Impact on Diagnostic and Therapeutic Applications

Michael Masoomi

Personal profile

External positions

Fingerprint

Collaborations and top research areas from the last five years

Projects

Developing A Novel Deep Learning Technique using Convolutional Neural Network (CNN) for Automated Diagnosis and Differentiating Lung Infections on Chest X-ray.

3D Volume Rendering Model and Pixelated Quantitative CT for Accurate Assessment of the Extent and Severity of Patients with COVID-19

Establishment of National DRL for CT in Hybrid Imaging Studies "The Second Phase of National NM CT (PET) Dose Audit for KW population – 2019.

Diagnostic Accuracy and Impact of F18-LDOPA With TOF PET-CT in Assessing Preoperative Management of Neonatal Hyperinsulinism, "A Non-Invasive Approach"

A Novel Voxel Based Quantitation in Identifying Scintigraphy Bone Lesions and its Potential Impact on Diagnostic and Therapeutic Applications

Research output