Ingenuity core ct scanner

Manufactured by Philips

The Ingenuity Core CT scanner is a medical imaging device manufactured by Philips. It utilizes computed tomography (CT) technology to capture high-quality, three-dimensional images of the internal structures of the human body. The scanner's core function is to provide healthcare professionals with detailed visual information to aid in the diagnosis and treatment of various medical conditions.

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Ingenuity CT (27 citations) Philips Ingenuity Core (11 citations) CT scanners (6 citations) Ingenuity CT scanner (3 citations)

2 protocols using ingenuity core ct scanner

Acute Stroke Brain CT Imaging Protocol

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The WhatsStroke study was designed following the guidelines of the Standards for Reporting of Diagnostic Accuracy initiative. 4 (link) First brain CT scans (including CT angiography if available) were collected from patients presenting with symptoms of acute stroke (<6 hours of symptom onset, before any recanalizing treatment) at the Christian Medical College, Ludhiana, India (between January 2018 and April 2019). Images were acquired using a Philips Ingenuity Core CT scanner. They were displayed on a 19-inch dual liquid crystal display diagnostic monitor with a resolution set to 2560×1024 and a screen refresh rate of 75 Hz.

Kalra L.P., Khatter H., Kulkarni A., Sahonta R., Rathore S., Hattingen E., You S.J., Wagner M., Weidauer S., Keil F., Pandian J.D, & Foerch C. (2022). Reliability of Instant Messaging-Based Evaluation of Brain Imaging in Acute Stroke. Stroke, 53(7).

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COVID-19 Lung CT Image Analysis Protocol

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CT images were collected using a Philips Ingenuity Core CT Scanner, while patients were in a deep inspiration breath-hold (DIBH) supine position. The patients were not given any oral contrast or intravenous agents. The CT scan was done at 120 kV, 225 mAs. The spiral pitch factor, gantry rotation time, and detector configurations were fixed at 1.08, 0.5 s, and 65 × 0.625, respectively. A 768 × 768 lung window and a 512 × 512 mediastinal window size, were used to reconstruct 1-mm-thick images with soft tissue kernel. The CT images were reviewed using twin 35 × 43 EIZO PACS displays with a 2048 × 1536 matrix. The final data comprised 2788 CT images for CoP patients and 990 CT images for NCoP patients. For 100 COVID-19 patients, we took 27–28 scans per patient which helped us obtain 100*27–100*28, i.e., 2758 CT scans. Similarly, for healthy patients, we took around 33 scans for each of 30 patients, resulting in 30*33 = 990 CT scans.

Saba L., Agarwal M., Patrick A., Puvvula A., Gupta S.K., Carriero A., Laird J.R., Kitas G.D., Johri A.M., Balestrieri A., Falaschi Z., Paschè A., Viswanathan V., El-Baz A., Alam I., Jain A., Naidu S., Oberleitner R., Khanna N.N., Bit A., Fatemi M., Alizad A, & Suri J.S. (2021). Six artificial intelligence paradigms for tissue characterisation and classification of non-COVID-19 pneumonia against COVID-19 pneumonia in computed tomography lungs. International Journal of Computer Assisted Radiology and Surgery, 16(3), 423-434.

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