AIMC Topic: Image Processing, Computer-Assisted

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Automated Segmentation of Graft Material in 1-Stage Sinus Lift Based on Artificial Intelligence: A Retrospective Study.

Clinical implant dentistry and related research
OBJECTIVES: Accurate assessment of postoperative bone graft material changes after the 1-stage sinus lift is crucial for evaluating long-term implant survival. However, traditional manual labeling and segmentation of cone-beam computed tomography (CB...

Dual biomarkers CT-based deep learning model incorporating intrathoracic fat for discriminating benign and malignant pulmonary nodules in multi-center cohorts.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
BACKGROUND: Recent studies in the field of lung cancer have emphasized the important role of body composition, particularly fatty tissue, as a prognostic factor. However, there is still a lack of practice in combining fatty tissue to discriminate ben...

Exploring hyperspectral anomaly detection with human vision: A small target aware detector.

Neural networks : the official journal of the International Neural Network Society
Hyperspectral anomaly detection (HAD) aims to localize pixel points whose spectral features differ from the background. HAD is essential in scenarios of unknown or camouflaged target features, such as water quality monitoring, crop growth monitoring ...

Dynamic graph consistency and self-contrast learning for semi-supervised medical image segmentation.

Neural networks : the official journal of the International Neural Network Society
Semi-supervised medical image segmentation endeavors to exploit a limited set of labeled data in conjunction with a substantial corpus of unlabeled data, with the aim of training models that can match or even exceed the efficacy of fully supervised s...

CT image super-resolution under the guidance of deep gradient information.

Journal of X-ray science and technology
Due to the hardware constraints of Computed Tomography (CT) imaging, acquiring high-resolution (HR) CT images in clinical settings poses a significant challenge. In recent years, convolutional neural networks have shown great potential in CT super-re...

Online monitoring of Haematococcus lacustris cell cycle using machine and deep learning techniques.

Bioresource technology
Optimal control and process optimization of astaxanthin production from Haematococcuslacustris is directly linked to its complex cell cycle ranging from vegetative green cells to astaxanthin-rich cysts. This study developed an automated online monito...

NAILS: Normalized Artificial Intelligence Labeling Sensor for Self-Care Health.

Sensors (Basel, Switzerland)
Visual examination of nails can reflect human health status. Diseases such as nutritive imbalances and skin diseases can be identified by looking at the colors around the plate part of the nails. We present the AI-based NAILS method to detect fingern...

Radiomics and Artificial Intelligence Landscape for [F]FDG PET/CT in Multiple Myeloma.

Seminars in nuclear medicine
[F]FDG PET/CT is a powerful imaging modality of high performance in multiple myeloma (MM) and is considered the appropriate method for assessing treatment response in this disease. On the other hand, due to the heterogeneous and sometimes complex pat...

Enhancing space-time video super-resolution via spatial-temporal feature interaction.

Neural networks : the official journal of the International Neural Network Society
The target of space-time video super-resolution (STVSR) is to increase both the frame rate (also referred to as the temporal resolution) and the spatial resolution of a given video. Recent approaches solve STVSR using end-to-end deep neural networks....

Conditional generative diffusion deep learning for accelerated diffusion tensor and kurtosis imaging.

Magnetic resonance imaging
PURPOSE: The purpose of this study was to develop DiffDL, a generative diffusion probabilistic model designed to produce high-quality diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) metrics from a reduced set of diffusion-weighted...