AIMC Topic: Deep Learning

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Deep-learning-based methods of attenuation correction for SPECT and PET.

Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
Attenuation correction (AC) is essential for quantitative analysis and clinical diagnosis of single-photon emission computed tomography (SPECT) and positron emission tomography (PET). In clinical practice, computed tomography (CT) is utilized to gene...

Deep Learning-Based Digitally Reconstructed Tomography of the Chest in the Evaluation of Solitary Pulmonary Nodules: A Feasibility Study.

Academic radiology
RATIONALE AND OBJECTIVES: Computed tomography (CT) is preferred for evaluating solitary pulmonary nodules (SPNs) but access or availability may be lacking, in addition, overlapping anatomy can hinder detection of SPNs on chest radiographs. We develop...

Ensemble deep learning model for predicting anterior cruciate ligament tear from lateral knee radiograph.

Skeletal radiology
OBJECTIVE: To develop an ensemble deep learning model (DLM) predicting anterior cruciate ligament (ACL) tears from lateral knee radiographs and to evaluate its diagnostic performance.

Benchmarking Deep Learning Models for Tooth Structure Segmentation.

Journal of dental research
A wide range of deep learning (DL) architectures with varying depths are available, with developers usually choosing one or a few of them for their specific task in a nonsystematic way. Benchmarking (i.e., the systematic comparison of state-of-the ar...

Deep learning for image-based liver analysis - A comprehensive review focusing on malignant lesions.

Artificial intelligence in medicine
Deep learning-based methods, in particular, convolutional neural networks and fully convolutional networks are now widely used in the medical image analysis domain. The scope of this review focuses on the analysis using deep learning of focal liver l...

Automatic Cobb angle measurement method based on vertebra segmentation by deep learning.

Medical & biological engineering & computing
The accuracy of the Cobb measurement is essential for the diagnosis and treatment of scoliosis. Manual measurement is however influenced by the observer variability hence affecting progression evaluation. In this paper, we propose a fully automatic C...

Deep learning based time-to-event analysis with PET, CT and joint PET/CT for head and neck cancer prognosis.

Computer methods and programs in biomedicine
OBJECTIVES: Recent studies have shown that deep learning based on pre-treatment positron emission tomography (PET) or computed tomography (CT) is promising for distant metastasis (DM) and overall survival (OS) prognosis in head and neck cancer (HNC)....

Deep learning-based in vivo dose verification from proton-induced secondary-electron-bremsstrahlung images with various count level.

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)
PURPOSE: Proton-induced secondary-electron-bremsstrahlung (SEB) imaging is a promising method for estimating the ranges of particle beam. However, SEB images do not directly represent dose distributions of particle beams. In addition, the ranges esti...

Deep Learning Approach to Impact Classification in Sensorized Panels Using Self-Attention.

Sensors (Basel, Switzerland)
This paper proposes a new method of impact classification for a Structural Health Monitoring system through the use of Self-Attention, the central building block of the Transformer neural network. As a topical and highly promising neural network arch...