AIMC Topic: Deep Learning

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Automatic thoracic aorta calcium quantification using deep learning in non-contrast ECG-gated CT images.

Biomedical physics & engineering express
Thoracic aorta calcium (TAC) can be assessed from cardiac computed tomography (CT) studies to improve cardiovascular risk prediction. The aim of this study was to develop a fully automatic system to detect TAC and to evaluate its performance for clas...

End-to-end deep learning approach to mouse behavior classification from cortex-wide calcium imaging.

PLoS computational biology
Deep learning is a powerful tool for neural decoding, broadly applied to systems neuroscience and clinical studies. Interpretable and transparent models that can explain neural decoding for intended behaviors are crucial to identifying essential feat...

Unraveling trends in schistosomiasis: deep learning insights into national control programs in China.

Epidemiology and health
OBJECTIVES: To achieve the ambitious goal of eliminating schistosome infections, the Chinese government has implemented diverse control strategies. This study explored the progress of the 2 most recent national schistosomiasis control programs in an ...

Deep learning algorithm for the automated detection and classification of nasal cavity mass in nasal endoscopic images.

PloS one
Nasal endoscopy is routinely performed to distinguish the pathological types of masses. There is a lack of studies on deep learning algorithms for discriminating a wide range of endoscopic nasal cavity mass lesions. Therefore, we aimed to develop an ...

MIS-Net: A deep learning-based multi-class segmentation model for CT images.

PloS one
The accuracy of traditional CT image segmentation algorithms is hindered by issues such as low contrast and high noise in the images. While numerous scholars have introduced deep learning-based CT image segmentation algorithms, they still face challe...

Deep-learning reconstructed lumbar spine 3D MRI for surgical planning: pedicle screw placement and geometric measurements compared to CT.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society
PURPOSE: To test equivalency of deep-learning 3D lumbar spine MRI with "CT-like" contrast to CT for virtual pedicle screw planning and geometric measurements in robotic-navigated spinal surgery.

Automatic and robust estimation of sex and chronological age from panoramic radiographs using a multi-task deep learning network: a study on a South Korean population.

International journal of legal medicine
Sex and chronological age estimation are crucial in forensic investigations and research on individual identification. Although manual methods for sex and age estimation have been proposed, these processes are labor-intensive, time-consuming, and err...

Detection and coverage estimation of purple nutsedge in turf with image classification neural networks.

Pest management science
BACKGROUND: Accurate detection of weeds and estimation of their coverage is crucial for implementing precision herbicide applications. Deep learning (DL) techniques are typically used for weed detection and coverage estimation by analyzing informatio...

Deepm6A-MT: A deep learning-based method for identifying RNA N6-methyladenosine sites in multiple tissues.

Methods (San Diego, Calif.)
N6-methyladenosine (m6A) is the most prevalent, abundant, and conserved internal modification in the eukaryotic messenger RNA (mRNAs) and plays a crucial role in the cellular process. Although more than ten methods were developed for m6A detection ov...