An overview of deep learning approaches in chest radiograph
Chest X-ray (CXR) interpretations are conducted in hospitals and medical facilities on daily
basis. If the interpretation tasks were performed correctly, various vital medical conditions of …
basis. If the interpretation tasks were performed correctly, various vital medical conditions of …
A survey on artificial intelligence techniques for biomedical image analysis in skeleton-based forensic human identification
This paper represents the first survey on the application of AI techniques for the analysis of
biomedical images with forensic human identification purposes. Human identification is of …
biomedical images with forensic human identification purposes. Human identification is of …
Multiclass CBCT image segmentation for orthodontics with deep learning
Accurate segmentation of the jaw (ie, mandible and maxilla) and the teeth in cone beam
computed tomography (CBCT) scans is essential for orthodontic diagnosis and treatment …
computed tomography (CBCT) scans is essential for orthodontic diagnosis and treatment …
A deep learning based dual encoder–decoder framework for anatomical structure segmentation in chest X-ray images
Automated multi-organ segmentation plays an essential part in the computer-aided
diagnostic (CAD) of chest X-ray fluoroscopy. However, develo** a CAD system for the …
diagnostic (CAD) of chest X-ray fluoroscopy. However, develo** a CAD system for the …
CX-Net: an efficient ensemble semantic deep neural network for ROI identification from chest-x-ray images for COPD diagnosis
Automatic identification of salient features in large medical datasets, particularly in chest x-
ray (CXR) images, is a crucial research area. Accurately detecting critical findings such as …
ray (CXR) images, is a crucial research area. Accurately detecting critical findings such as …
A multi-objective segmentation method for chest X-rays based on collaborative learning from multiple partially annotated datasets
Accurate segmentation of multiple targets, such as ribs, clavicles, heart, and lung fields, from
chest X-ray images is crucial for diagnosing various lung diseases. Currently, mainstream …
chest X-ray images is crucial for diagnosing various lung diseases. Currently, mainstream …
Dense-Unet: a light model for lung fields segmentation in Chest X-Ray images
Automatic and accurate lung segmentation in chest X-ray (CXR) images is fundamental for
computer-aided diagnosis systems since the lung is the region of interest in many diseases …
computer-aided diagnosis systems since the lung is the region of interest in many diseases …
Robust classification from noisy labels: Integrating additional knowledge for chest radiography abnormality assessment
Chest radiography is the most common radiographic examination performed in daily clinical
practice for the detection of various heart and lung abnormalities. The large amount of data …
practice for the detection of various heart and lung abnormalities. The large amount of data …
MSLPNet: multi-scale location perception network for dental panoramic X-ray image segmentation
Tooth segmentation, as one of the key techniques of medical image segmentation, can be
widely applied to various medical applications, eg, orthodontic treatment, corpse …
widely applied to various medical applications, eg, orthodontic treatment, corpse …
Vision transformers for lung segmentation on CXR images
Accurate segmentation of the lungs in CXR images is the basis for an automated CXR
image analysis system. It helps radiologists in detecting lung areas, subtle signs of disease …
image analysis system. It helps radiologists in detecting lung areas, subtle signs of disease …