Head and Neck Imaging

Mar 16th, 2018Mar 17th, 2018

Melbourne, 07

AU

https://lightboxradiology.com/course-details.aspx?c=1114

Phone:+61754492717

Will outline the principles of image acquisition and interpretation of the head and neck. Imaging areas include the temporal bones and base of skull; paranasal sinus and airways; parotid, submandibular, and thyroid glands; vessels and nerves; and muscles and nodes.

2024 04 19 7 Year Old Boy With Autoimmune Sclerosing Cholangitis

MR elastography effective for assessing liver stiffness in children

April 19, 2024

Breast Mammography Scanner

High breast density tied to impaired recurrence-free cancer survival

April 19, 2024

FREE WEBINAR: Advanced visualization in 2024: Enhancing radiology care

FREE WEBINAR: Advanced visualization in 2024: Enhancing radiology care

April 17, 2024

PET/MRI reveals sex differences in patients with autism

April 18, 2024

MR elastography effective for assessing liver stiffness in children

By Kate Madden Yee

MR elastography is an effective technique for noninvasive monitoring of liver stiffness -- a surrogate for fibrosis -- in children and young adults with autoimmune liver disease, researchers have reported.

April 19, 2024

2024 04 19 7 Year Old Boy With Autoimmune Sclerosing Cholangitis

High breast density tied to impaired recurrence-free cancer survival

By Amerigo Allegretto

Recurrence-free breast cancer survival is less likely in women with high breast density compared with women with low density.

April 19, 2024

Breast Mammography Scanner

Can ChatGPT ‘data mine’ patient reports for stroke registries?

ChatGPT-4 appears useful for extracting details from reports on thrombectomy procedures in stroke patients, a labor-intensive and error-prone task currently performed by human readers.

April 19, 2024

Stroke Skull Xray 400

PET/MRI reveals sex differences in patients with autism

PET/MRI shows that young women with autism spectrum disorder have increased brain metabolism associated with translocator protein.

April 18, 2024

Radiologist consultation improves patients' LCS attitudes

By Kate Madden Yee

Consulting with a radiologist boosts patients' attitudes toward lung cancer screening (LCS) and their interest in quitting smoking, researchers have reported.

April 18, 2024

Doctor Female Young Desk 400

Pisano speaks with AuntMinnie.com on new ARPA-H leadership role

By Amerigo Allegretto

Etta Pisano, MD, spoke with AuntMinnie.com on leading the Advancing Clinical Trials Readiness initiative, part of ARPA-H.

April 18, 2024

Screenshot (1143)

AI proposed to help radiologists detect child abuse injuries

A team at Michigan State University has developed an AI model designed to detect rib fractures in children under 3 years old.

April 17, 2024

Test set images with ground truth (teal, red) and model predictions (green, yellow), with true positives (green), false positives (yellow), and false negatives (red). Predictions from the 6x-YOLOv5 ensemble trained on histogram equalized input images with a y = 0.2 avalanche scheme, achieving 0.536 precision, 0.795 recall, and 0.723 F2 score. Image and caption courtesy of Scientific Reports.

Tailored lung cancer screening model helps determine nodule follow-up

By Kate Madden Yee

A personalized lung cancer screening model used with patients with pulmonary nodules identified on low-dose CT helps clinicians determine how to follow up better than rule-based protocols, researchers have found.

April 17, 2024

POCUS used widely in lung ultrasound applications

By Amerigo Allegretto

Some of the top domains for users of point-of-care ultrasound (POCUS) incorporate the technology for lung ultrasound applications.

April 17, 2024

Screenshot (1142)

CT-based deep learning identifies patients at further lung cancer risk

By Kate Madden Yee

A CT-based deep learning model can identify individuals with clinical stage IA non-small cell lung cancer (NSCLC) at high risk of further disease, researchers have found.

April 16, 2024

ChatGPT-4 matches radiologists in flagging errors on reports

ChatGPT-4 matched radiologists when tasked with detecting errors in imaging reports, with the study suggesting the technology may be useful for improving reporting accuracy.

April 16, 2024

Deep-learning model determines breast tumor staging

By Amerigo Allegretto

A deep-learning model based on mammographic images can determine tumor staging and sentinel lymph node metastasis in breast cancer patients.

April 16, 2024

Researchers explain the data preparation and structure of a proposed CNN-based deep learning model using mammography features to determine breast tumor staging. The image is available for use under a Creative Commons license: CC BY-NC-ND 4.0 DEED Attribution-NonCommercial-NoDerivs 4.0 International.

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