AI Medical Compendium Journal:
International journal of computer assisted radiology and surgery

Showing 61 to 70 of 481 articles

Shape completion in the dark: completing vertebrae morphology from 3D ultrasound.

International journal of computer assisted radiology and surgery
PURPOSE: Ultrasound (US) imaging, while advantageous for its radiation-free nature, is challenging to interpret due to only partially visible organs and a lack of complete 3D information. While performing US-based diagnosis or investigation, medical ...

Robust prostate disease classification using transformers with discrete representations.

International journal of computer assisted radiology and surgery
PURPOSE: Automated prostate disease classification on multi-parametric MRI has recently shown promising results with the use of convolutional neural networks (CNNs). The vision transformer (ViT) is a convolutional free architecture which only exploit...

Enhancing surgical instrument segmentation: integrating vision transformer insights with adapter.

International journal of computer assisted radiology and surgery
PURPOSE: In surgical image segmentation, a major challenge is the extensive time and resources required to gather large-scale annotated datasets. Given the scarcity of annotated data in this field, our work aims to develop a model that achieves compe...

Toward confident prostate cancer detection using ultrasound: a multi-center study.

International journal of computer assisted radiology and surgery
PURPOSE: Deep learning-based analysis of micro-ultrasound images to detect cancerous lesions is a promising tool for improving prostate cancer (PCa) diagnosis. An ideal model should confidently identify cancer while responding with appropriate uncert...

Parameter-efficient framework for surgical action triplet recognition.

International journal of computer assisted radiology and surgery
PURPOSE: Surgical action triplet recognition is a clinically significant yet challenging task. It provides surgeons with detailed information about surgical scenarios, thereby facilitating clinical decision-making. However, the high similarity among ...

One model to use them all: training a segmentation model with complementary datasets.

International journal of computer assisted radiology and surgery
PURPOSE: Understanding surgical scenes is crucial for computer-assisted surgery systems to provide intelligent assistance functionality. One way of achieving this is via scene segmentation using machine learning (ML). However, such ML models require ...

From quantitative metrics to clinical success: assessing the utility of deep learning for tumor segmentation in breast surgery.

International journal of computer assisted radiology and surgery
PURPOSE: Preventing positive margins is essential for ensuring favorable patient outcomes following breast-conserving surgery (BCS). Deep learning has the potential to enable this by automatically contouring the tumor and guiding resection in real ti...

Minimizing possible negative effects of artificial intelligence.

International journal of computer assisted radiology and surgery

LensePro: label noise-tolerant prototype-based network for improving cancer detection in prostate ultrasound with limited annotations.

International journal of computer assisted radiology and surgery
PURPOSE: The standard of care for prostate cancer (PCa) diagnosis is the histopathological analysis of tissue samples obtained via transrectal ultrasound (TRUS) guided biopsy. Models built with deep neural networks (DNNs) hold the potential for direc...

Deep-learning based 3D reconstruction of lower limb bones from biplanar radiographs for preoperative osteotomy planning.

International journal of computer assisted radiology and surgery
PURPOSE: Three-dimensional (3D) preoperative planning has become the gold standard for orthopedic surgeries, primarily relying on CT-reconstructed 3D models. However, in contrast to standing radiographs, a CT scan is not part of the standard protocol...