AIMC Topic: Ultrasonography

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Attention residual network for medical ultrasound image segmentation.

Scientific reports
Ultrasound imaging can distinctly display the morphology and structure of internal organs within the human body, enabling the examination of organs like the breast, liver, and thyroid. It can identify the locations of tumors, nodules, and other lesio...

A superpixel based self-attention network for uterine fibroid segmentation in high intensity focused ultrasound guidance images.

Scientific reports
Ultrasound guidance images are widely used for high intensity focused ultrasound (HIFU) therapy; however, the speckles, acoustic shadows, and signal attenuation in ultrasound guidance images hinder the observation of the images by radiologists and ma...

Ultrasound-based classification of follicular thyroid Cancer using deep convolutional neural networks with transfer learning.

Scientific reports
This study aimed to develop and validate convolutional neural network (CNN) models for distinguishing follicular thyroid carcinoma (FTC) from follicular thyroid adenoma (FTA). Additionally, this current study compared the performance of CNN models wi...

Enhancing ultrasonographic detection of hepatocellular carcinoma with artificial intelligence: current applications, challenges and future directions.

BMJ open gastroenterology
BACKGROUND: Hepatocellular carcinoma (HCC) remains a leading cause of cancer-related mortality worldwide, with early detection playing a crucial role in improving survival rates. Artificial intelligence (AI), particularly in medical image analysis, h...

Novel Artificial Intelligence-Driven Infant Meningitis Screening From High-Resolution Ultrasound Imaging.

Ultrasound in medicine & biology
BACKGROUND: Infant meningitis can be a life-threatening disease and requires prompt and accurate diagnosis to prevent severe outcomes or death. Gold-standard diagnosis requires lumbar puncture (LP) to obtain and analyze cerebrospinal fluid (CSF). Des...

FeaCL: Carotid plaque classification from ultrasound images using feature-level and instance-level contrast learning.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
The classification of carotid plaques from ultrasound images in clinical application is crucial for predicting patient risks of cardiovascular and cerebrovascular diseases, as well as for developing appropriate treatment strategies. Although the effe...

SE-ATT-YOLO- A deep learning driven ultrasound based respiratory motion compensation system for precision radiotherapy.

Computers in biology and medicine
OBJECTIVE: The therapeutic management of neoplasm employs high level energy beam to ablate malignant cells, which can cause collateral damage to adjacent normal tissue. Furthermore, respiration-induced organ motion, during radiotherapy can lead to si...

Morphological characterization of median nerve and transverse carpal ligament from ultrasound images using convolutional neural networks.

Medical engineering & physics
OBJECTIVES: The purpose of this study was to automatically segment and quantify the median nerve and carpal arch from ultrasound images using convolutional neural network (CNN).

LoRA-Enhanced RT-DETR: First Low-Rank Adaptation based DETR for real-time full body anatomical structures identification in musculoskeletal ultrasound.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Medical imaging models for object identification often rely on extensive pretraining data, which is difficult to obtain due to data scarcity and privacy constraints. In practice, hospitals typically have access only to pretrained model weights withou...