Pregnancy

Deep-Learning-Based Color Doppler Ultrasound Image Feature in the Diagnosis of Elderly Patients with Chronic Heart Failure Complicated with Sarcopenia.

The neural network algorithm of deep learning was applied to optimize and improve color Doppler ultrasound images, which was used for the research on elderly patients with chronic heart failure (CHF) complicated with sarcopenia, so as to analyze the effect of the deep-learning-based color Doppler ultrasound image on the diagnosis of CHF. 259 patients were selected randomly in this study, who were ...

A Deep Learning-Based Automatic First-Arrival Picking Method for Ultrasound Sound-Speed Tomography.

Ultrasound sound-speed tomography (USST) has shown great prospects for breast cancer diagnosis due to its advantages of nonradiation, low cost, 3-D breast images, and quantitative indicators. However, the reconstruction quality of USST is highly dependent on the first-arrival picking of the transmission wave. Traditional first-arrival picking methods have low accuracy and noise robustness. To impr...

Ultrasound Scatterer Density Classification Using Convolutional Neural Networks and Patch Statistics.

Quantitative ultrasound (QUS) can reveal crucial information on tissue properties, such as scatterer density. If the scatterer density per resolution ...

Three artificial intelligence data challenges based on CT and ultrasound.

PURPOSE: The 2020 edition of these Data Challenges was organized by the French Society of Radiology (SFR), from September 28 to September 30, 2020. Th...

Conversation-Based Information Delivery Method for Facility Management.

Facility management platforms are widely used in the facility maintenance phase of the building life cycle. However, a large amount of complex buildin...

Ethics of AI in Pathology: Current Paradigms and Emerging Issues.

Deep learning has rapidly advanced artificial intelligence (AI) and algorithmic decision-making (ADM) paradigms, affecting many traditional fields of ...

Loop-mediated isothermal amplification (LAMP) and machine learning application for early pregnancy detection using bovine vaginal mucosal membrane.

An early and accurate pregnancy diagnosis method is required to improve the reproductive performance of cows. Here we developed an easy pregnancy dete...

Pregnancy prediction performance of an annotation-free embryo scoring system on the basis of deep learning after single vitrified-warmed blastocyst transfer: a single-center large cohort retrospective study.

OBJECTIVE: To analyze the performance of an annotation-free embryo scoring system on the basis of deep learning for pregnancy prediction after single ...

Automatic fetal biometry prediction using a novel deep convolutional network architecture.

PURPOSE: Fetal biometric measurements face a number of challenges, including the presence of speckle, limited soft-tissue contrast and difficulties in...

Deep-Learning-Driven Full-Waveform Inversion for Ultrasound Breast Imaging.

Ultrasound breast imaging is a promising alternative to conventional mammography because it does not expose women to harmful ionising radiation and it...

Deep Learning-Based Carotid Plaque Segmentation from B-Mode Ultrasound Images.

Carotid ultrasound measurement of total plaque area (TPA) provides a method for quantifying carotid plaque burden and monitoring changes in carotid at...

Deep learning segmentation of transverse musculoskeletal ultrasound images for neuromuscular disease assessment.

Ultrasound imaging is a patient-friendly and robust technique for studying physiological and pathological muscles. An automatic deep learning (DL) sys...

Establish a normal fetal lung gestational age grading model and explore the potential value of deep learning algorithms in fetal lung maturity evaluation.

BACKGROUND: Prenatal evaluation of fetal lung maturity (FLM) is a challenge, and an effective non-invasive method for prenatal assessment of FLM is ne...

Cross Attention Squeeze Excitation Network (CASE-Net) for Whole Body Fetal MRI Segmentation.

Segmentation of the fetus from 2-dimensional (2D) magnetic resonance imaging (MRI) can aid radiologists with clinical decision making for disease diag...

A Deep Learning Approach for Segmentation, Classification, and Visualization of 3-D High-Frequency Ultrasound Images of Mouse Embryos.

Segmentation and mutant classification of high-frequency ultrasound (HFU) mouse embryo brain ventricle (BV) and body images can provide valuable infor...

Quantitative Analysis and Automated Lung Ultrasound Scoring for Evaluating COVID-19 Pneumonia With Neural Networks.

As being radiation-free, portable, and capable of repetitive use, ultrasonography is playing an important role in diagnosing and evaluating the COVID-...

An Automatic Biopsy Needle Detection and Segmentation on Ultrasound Images Using a Convolutional Neural Network.

Needle visualization in the ultrasound image is essential to successfully perform the ultrasound-guided core needle biopsy. Automatic needle detection...

Serum Bile Acids in Intrahepatic Cholestasis of Pregnancy (ICP), Versus Pregnant and Nonpregnant Controls in Asian Indian Women and a Proposed Scoring to Optimize Management in ICP.

OBJECTIVES: This prospective clinical trial was conducted to assess serum bile acids (BA) levels in women with intrahepatic cholestasis of pregnancy (...

Embryo selection with artificial intelligence: how to evaluate and compare methods?

Embryo selection within in vitro fertilization (IVF) is the process of evaluating qualities of fertilized oocytes (embryos) and selecting the best emb...

Self-assembly of diclofenac prodrug into nanomicelles for enhancing the anti-inflammatory activity.

Non-steroidal anti-inflammatory drugs (NSAIDs) are widely prescribed for the treatment of various types of inflammatory conditions. Diclofenac is a ve...