AIMC Topic: Image Processing, Computer-Assisted

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Autologous Transplantation Tooth Guide Design Based on Deep Learning.

Journal of oral and maxillofacial surgery : official journal of the American Association of Oral and Maxillofacial Surgeons
BACKGROUND: Autologous tooth transplantation requires precise surgical guide design, involving manual tracing of donor tooth contours based on patient cone-beam computed tomography (CBCT) scans. While manual corrections are time-consuming and prone t...

Cross-domain mechanism for few-shot object detection on Urine Sediment Image.

Computers in biology and medicine
Deep learning object detection networks require a large amount of box annotation data for training, which is difficult to obtain in the medical image field. The few-shot object detection algorithm is significant for an unseen category, which can be i...

Real-time semantic segmentation and anomaly detection of functional images for cell therapy manufacturing.

Cytotherapy
BACKGROUND AIMS: Cell therapy is a promising treatment method that uses living cells to address a variety of diseases and conditions, including cardiovascular diseases, neurologic disorders and certain cancers. As interest in cell therapy grows, ther...

Statistically unbiased prediction enables accurate denoising of voltage imaging data.

Nature methods
Here we report SUPPORT (statistically unbiased prediction utilizing spatiotemporal information in imaging data), a self-supervised learning method for removing Poisson-Gaussian noise in voltage imaging data. SUPPORT is based on the insight that a pix...

Validation of deep learning-based CT image reconstruction for treatment planning.

Scientific reports
Deep learning-based CT image reconstruction (DLR) is a state-of-the-art method for obtaining CT images. This study aimed to evaluate the usefulness of DLR in radiotherapy. Data were acquired using a large-bore CT system and an electron density phanto...

Region of interest focused MRI to synthetic CT translation using regression and segmentation multi-task network.

Physics in medicine and biology
. In MR-only clinical workflow, replacing CT with MR image is of advantage for workflow efficiency and reduces radiation to the patient. An important step required to eliminate CT scan from the workflow is to generate the information provided by CT v...

A deep sift convolutional neural networks for total brain volume estimation from 3D ultrasound images.

Computer methods and programs in biomedicine
Preterm infants are a highly vulnerable population. The total brain volume (TBV) of these infants can be accurately estimated by brain ultrasound (US) imaging which enables a longitudinal study of early brain growth during Neonatal Intensive Care (NI...

Deep learning-based pigment analysis model trained with optical approach and ground truth assistance.

Journal of biophotonics
This study introduces an integrated training method combining the optical approach with ground truth for skin pigment analysis. Deep learning is increasingly applied to skin pigment analysis, primarily melanin and hemoglobin. While regression analysi...

Deep learning in MRI-guided radiation therapy: A systematic review.

Journal of applied clinical medical physics
Recent advances in MRI-guided radiation therapy (MRgRT) and deep learning techniques encourage fully adaptive radiation therapy (ART), real-time MRI monitoring, and the MRI-only treatment planning workflow. Given the rapid growth and emergence of new...

Automating Ground Truth Annotations for Gland Segmentation Through Immunohistochemistry.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Microscopic evaluation of glands in the colon is of utmost importance in the diagnosis of inflammatory bowel disease and cancer. When properly trained, deep learning pipelines can provide a systematic, reproducible, and quantitative assessment of dis...