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Nov 25, 2012
Latest in Advanced Visualization
Computer Brain Money
See All AI raises $33M for 3D visualization platform
May 28, 2025
Erick Torres, MD, describes a 3D-printed simulation model he and colleagues created, which results show marked improvement in accurate needle targeting among medical students and residents performing ultrasound-guided regional anesthesia.
AIUM: 3D-printed training model improves ultrasound-guided anesthesia
March 31, 2025
Colon
CTC for colorectal cancer screening is at an 'inflection point'
March 12, 2025
MRI scans show two areas of clinically significant prostate cancer in a 65-year-old man with a prostate-specific antigen level of 8.23 ng/mL. Images are (A, E) axial T2-weighted images, (B, F) axial diffusion-weighted images obtained with a b value of 1500 sec/mm2, (C, G) axial apparent diffusion coefficient images, and (D, H) lesion masks generated by the deep learning algorithm (DLA) on T2-weighted images. The DLA detected a lesion in the right posteromedial peripheral zone of the apex (D), which was assigned as Prostate Imaging Reporting and Data System (PI-RADS) 4. A radiologist also detected the lesion and assigned it PI-RADS 4 (arrow in A-C). A lesion in the right anterior transition zone (H) was detected by the DLA, which was assigned PI-RADS 4. The radiologist did not detect the lesion (arrow in E-G). Both lesions were confirmed as prostate cancer with Gleason grade group 2. Caption and image courtesy of RSNA.
DL algorithm targeting prostate cancer demonstrates clinical impact
March 12, 2025
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See All AI raises $33M for 3D visualization platform
Medtech developer See All AI has raised $33 million for the development and commercialization of its AI-based platform.
May 28, 2025
Computer Brain Money
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A 3D-printed simulation model could help improve ultrasound-guided anesthesia.
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Erick Torres, MD, describes a 3D-printed simulation model he and colleagues created, which results show marked improvement in accurate needle targeting among medical students and residents performing ultrasound-guided regional anesthesia.
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DL algorithm targeting prostate cancer demonstrates clinical impact
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Per participant, a deep-learning (DL) algorithm demonstrated increased specificity of 64.8% compared with radiologists at 21.3%.
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MRI scans show two areas of clinically significant prostate cancer in a 65-year-old man with a prostate-specific antigen level of 8.23 ng/mL. Images are (A, E) axial T2-weighted images, (B, F) axial diffusion-weighted images obtained with a b value of 1500 sec/mm2, (C, G) axial apparent diffusion coefficient images, and (D, H) lesion masks generated by the deep learning algorithm (DLA) on T2-weighted images. The DLA detected a lesion in the right posteromedial peripheral zone of the apex (D), which was assigned as Prostate Imaging Reporting and Data System (PI-RADS) 4. A radiologist also detected the lesion and assigned it PI-RADS 4 (arrow in A-C). A lesion in the right anterior transition zone (H) was detected by the DLA, which was assigned PI-RADS 4. The radiologist did not detect the lesion (arrow in E-G). Both lesions were confirmed as prostate cancer with Gleason grade group 2. Caption and image courtesy of RSNA.
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3D printing increases user confidence, saves on procedure times
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