AIMC Topic: Image Interpretation, Computer-Assisted

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Prediction of Total Knee Replacement and Diagnosis of Osteoarthritis by Using Deep Learning on Knee Radiographs: Data from the Osteoarthritis Initiative.

Radiology
Background The methods for assessing knee osteoarthritis (OA) do not provide enough comprehensive information to make robust and accurate outcome predictions. Purpose To develop a deep learning (DL) prediction model for risk of OA progression by usin...

Dense anatomical annotation of slit-lamp images improves the performance of deep learning for the diagnosis of ophthalmic disorders.

Nature biomedical engineering
The development of artificial intelligence algorithms typically demands abundant high-quality data. In medicine, the datasets that are required to train the algorithms are often collected for a single task, such as image-level classification. Here, w...

Superpixel-based deep convolutional neural networks and active contour model for automatic prostate segmentation on 3D MRI scans.

Medical & biological engineering & computing
Automatic and reliable prostate segmentation is an essential prerequisite for assisting the diagnosis and treatment, such as guiding biopsy procedure and radiation therapy. Nonetheless, automatic segmentation is challenging due to the lack of clear p...

The future of pathology is digital.

Pathology, research and practice
Information, archives, and intelligent artificial systems are part of everyday life in modern medicine. They already support medical staff by mapping their workflows with shared availability of cases' referral information, as needed for example, by t...

Ensemble Deep Learning Model for Multicenter Classification of Thyroid Nodules on Ultrasound Images.

Medical science monitor : international medical journal of experimental and clinical research
BACKGROUND Thyroid nodules are extremely common and typically diagnosed with ultrasound whether benign or malignant. Imaging diagnosis assisted by Artificial Intelligence has attracted much attention in recent years. The aim of our study was to build...

Lower Adenoma Miss Rate of Computer-Aided Detection-Assisted Colonoscopy vs Routine White-Light Colonoscopy in a Prospective Tandem Study.

Gastroenterology
BACKGROUND AND AIMS: Up to 30% of adenomas might be missed during screening colonoscopy-these could be polyps that appear on-screen but are not recognized by endoscopists or polyps that are in locations that do not appear on the screen at all. Comput...

Utilizing artificial intelligence in endoscopy: a clinician's guide.

Expert review of gastroenterology & hepatology
INTRODUCTION: Artificial intelligence (AI) that surpasses human ability in image recognition is expected to be applied in the field of gastrointestinal endoscopes. Accordingly, its research and development (R &D) is being actively conducted. With the...

Artificial Intelligence Medical Ultrasound Equipment: Application of Breast Lesions Detection.

Ultrasonic imaging
Breast cancer ranks first among cancers affecting women's health. Our work aims to realize the intelligence of the medical ultrasound equipment with limited computational capability, which is used for the assistant detection of breast lesions. We emb...

Identification of areas of grading difficulties in prostate cancer and comparison with artificial intelligence assisted grading.

Virchows Archiv : an international journal of pathology
The International Society of Urological Pathology (ISUP) hosts a reference image database supervised by experts with the purpose of establishing an international standard in prostate cancer grading. Here, we aimed to identify areas of grading difficu...