AIMC Topic: Deep Learning

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A scoping review on multimodal deep learning in biomedical images and texts.

Journal of biomedical informatics
OBJECTIVE: Computer-assisted diagnostic and prognostic systems of the future should be capable of simultaneously processing multimodal data. Multimodal deep learning (MDL), which involves the integration of multiple sources of data, such as images an...

Deep Learning Ultrasound Computed Tomography Under Sparse Sampling.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Ultrasound computed tomography (USCT) is a fast-emerging imaging modality that is expected to help detect and characterize breast tumors by quantifying the distribution of the speed of sound (SOS) and acoustic attenuation in breast tissue. High-quali...

The Big Bang of Deep Learning in Ultrasound-Guided Surgery: A Review.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Ultrasound (US) imaging is a paramount modality in many image-guided surgeries and percutaneous interventions, thanks to its high portability, temporal resolution, and cost-efficiency. However, due to its imaging principles, the US is often noisy and...

Ultrasound Frame-to-Volume Registration via Deep Learning for Interventional Guidance.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Fusing intraoperative 2-D ultrasound (US) frames with preoperative 3-D magnetic resonance (MR) images for guiding interventions has become the clinical gold standard in image-guided prostate cancer biopsy. However, developing an automatic image regis...

Deep Learning in the Recognition of Activities of Daily Living Using Smartwatch Data.

Sensors (Basel, Switzerland)
The recognition of human activities (HAR) using wearable device data, such as smartwatches, has gained significant attention in the field of computer science due to its potential to provide insights into individuals' daily activities. This article ai...

Reproducibility analysis of automated deep learning based localisation of mandibular canals on a temporal CBCT dataset.

Scientific reports
Preoperative radiological identification of mandibular canals is essential for maxillofacial surgery. This study demonstrates the reproducibility of a deep learning system (DLS) by evaluating its localisation performance on 165 heterogeneous cone bea...

Geometric evaluations of CT and MRI based deep learning segmentation for brain OARs in radiotherapy.

Physics in medicine and biology
Deep-learning auto-contouring (DL-AC) promises standardisation of organ-at-risk (OAR) contouring, enhancing quality and improving efficiency in radiotherapy. No commercial models exist for OAR contouring based on brain magnetic resonance imaging (MRI...

Deep learning algorithm for visual quality assessment of the spirograms.

Physiological measurement
. The quality of spirometry manoeuvres is crucial for correctly interpreting the values of spirometry parameters. A fundamental guideline for proper quality assessment is the American Thoracic Society and European Respiratory Society (ATS/ERS) Standa...