Breast Cancer

Deep learning image reconstruction algorithm for abdominal multidetector CT at different tube voltages: assessment of image quality and radiation dose in a phantom study.

OBJECTIVES: To compare the image quality and radiation dose of a deep learning image reconstruction (DLIR) algorithm compared with iterative reconstruction (IR) and filtered back projection (FBP) at different tube voltages and tube currents.

High-strength deep learning image reconstruction in coronary CT angiography at 70-kVp tube voltage significantly improves image quality and reduces both radiation and contrast doses.

OBJECTIVES: To explore the use of 70-kVp tube voltage combined with high-strength deep learning image reconstruction (DLIR-H) in reducing radiation and contrast doses in coronary CT angiography (CCTA) in patients with body mass index (BMI) < 26 kg/m, in comparison with the conventional scan protocol using 120 kVp and adaptive statistical iterative reconstruction (ASIR-V).

Artificial intelligence: A promising frontier in bladder cancer diagnosis and outcome prediction.

Bladder cancer (BCa) is the most common malignancy of the urinary tract and the most expensive malignancy to treat over the patients' lifetime. In rec...

Single-Port Retzius-Sparing Robot-Assisted Radical Prostatectomy: Feasibility and Early Outcomes.

To determine safety and feasibility of single-port Retzius-sparing robot-assisted radical prostatectomy (SP-rsRARP) using the da Vinci SP (Intuitive ...

Magnetic Biohybrid Microrobot Multimers Based on Cells for Enhanced Targeted Drug Delivery.

Magnetic micro-/nanorobots have been regarded as a promising platform for targeted drug delivery, and tremendous strategies have been developed in rec...

Reduced-Dose Deep Learning Reconstruction for Abdominal CT of Liver Metastases.

Background Assessment of liver lesions is constrained as CT radiation doses are lowered; evidence suggests deep learning reconstructions mitigate such...

Prediction of Lung Infection during Palliative Chemotherapy of Lung Cancer Based on Artificial Neural Network.

Lung infection seriously affects the effect of chemotherapy in patients with lung cancer and increases pain. The study is aimed at establishing the pr...

Artificial intelligence for breast cancer analysis: Trends & directions.

Breast cancer is one of the leading causes of death among women. Early detection of breast cancer can significantly improve the lives of millions of w...

Reconstruction of three-dimensional tomographic patient models for radiation dose modulation in CT from two scout views using deep learning.

BACKGROUND: A tomographic patient model is essential for radiation dose modulation in x-ray computed tomography (CT). Currently, two-view scout images...

Improving generalisation capability of artificial intelligence-based solar radiation estimator models using a bio-inspired optimisation algorithm and multi-model approach.

One way of reducing environmental pollution is to reduce our dependence on fossil fuels by replacing them with solar radiation (Rs), which is one of t...

Breast Tumor Detection and Classification in Mammogram Images Using Modified YOLOv5 Network.

Breast cancer incidence has been rising steadily during the past few decades. It is the second leading cause of death in women. If it is diagnosed ear...

Artificial Intelligence-Guided Prediction of Dental Doses Before Planning of Radiation Therapy for Oropharyngeal Cancer: Technical Development and Initial Feasibility of Implementation.

PURPOSE: The aim was to develop a novel artificial intelligence (AI)-guided clinical decision support system, to predict radiation doses to subsites o...

Identifying Cancer Subtypes Using a Residual Graph Convolution Model on a Sample Similarity Network.

Cancer subtype classification helps us to understand the pathogenesis of cancer and develop new cancer drugs, treatment from which patients would bene...

Engineering naphthalimide-cyanine integrated near-infrared dye into ROS-responsive nanohybrids for tumor PDT/PTT/chemotherapy.

Photodynamic (PDT) and photothermal therapies (PTT) are emerging treatments for tumour ablation. Organic dyes such as porphyrin, chlorin, phthalocyani...

[EMPAIA-ecosystem for pathology diagnostics with AI assistance].

Applications of deep learning and other artificial intelligence techniques play an increasing role in pathological research. In contrast to research, ...

Radiation Protection and Occupational Exposure on Ga-PSMA-11-Based Cerenkov Luminescence Imaging Procedures in Robot-Assisted Prostatectomy.

Cerenkov luminescence imaging (CLI) was successfully implemented in the intraoperative context as a form of radioguided cancer surgery, showing promis...

Deep Learning for Radiotherapy Outcome Prediction Using Dose Data - A Review.

Artificial intelligence, and in particular deep learning using convolutional neural networks, has been used extensively for image classification and s...

Byzantine-robust federated learning via credibility assessment on non-IID data.

Federated learning is a novel framework that enables resource-constrained edge devices to jointly learn a model, which solves the problem of data prot...

A machine and human reader study on AI diagnosis model safety under attacks of adversarial images.

While active efforts are advancing medical artificial intelligence (AI) model development and clinical translation, safety issues of the AI models eme...

Radiation Dose Reduction in Digital Mammography by Deep-Learning Algorithm Image Reconstruction: A Preliminary Study.

PURPOSE: To develop a denoising convolutional neural network-based image processing technique and investigate its efficacy in diagnosing breast cancer...