相关论文: Autonomous Driving in the Lung using Deep Learning…
Pneumothorax is a critical condition that requires timely communication and immediate action. In order to prevent significant morbidity or patient death, early detection is crucial. For the task of pneumothorax detection, we study the…
The introduction of lung cancer screening programs will produce an unprecedented amount of chest CT scans in the near future, which radiologists will have to read in order to decide on a patient follow-up strategy. According to the current…
We developed a deep learning framework that helps to automatically identify and segment lung cancer areas in patients' tissue specimens. The study was based on a cohort of lung cancer patients operated at the Uppsala University Hospital.…
Pulmonary Embolisms (PE) represent a leading cause of cardiovascular death. While medical imaging, through computed tomographic pulmonary angiography (CTPA), represents the gold standard for PE diagnosis, it is still susceptible to…
Cancer is one of the leading causes of death globally, and early diagnosis is crucial for patient survival. Deep learning algorithms have great potential for automatic cancer analysis. Artificial intelligence has achieved high performance…
Cancer is the uncontrollable cell division of abnormal cells inside the human body, which can spread to other body organs. It is one of the non-communicable diseases (NCDs) and NCDs accounts for 71% of total deaths worldwide whereas lung…
Mobile robotics is a research area that has witnessed incredible advances for the last decades. Robot navigation is an essential task for mobile robots. Many methods are proposed for allowing robots to navigate within different…
Automated lobar segmentation allows regional evaluation of lung disease and is important for diagnosis and therapy planning. Advanced statistical workflows permitting such evaluation is a needed area within respiratory medicine; their…
Convolutional neural networks (CNNs) have shown great promise in improving computer aided detection (CADe). From classifying tumors found via mammography as benign or malignant to automated detection of colorectal polyps in CT colonography,…
Lung cancer remains one of the leading causes of cancer-related mortality worldwide. Conventional computed tomography (CT) imaging, while essential for detection and staging, has limitations in distinguishing benign from malignant lesions…
This paper introduces a novel deep-learning method for the automatic detection and segmentation of lung nodules, aimed at advancing the accuracy of early-stage lung cancer diagnosis. The proposed approach leverages a unique "Channel Squeeze…
Automated segmentation of anatomical structures is a crucial step in image analysis. For lung segmentation in computed tomography, a variety of approaches exist, involving sophisticated pipelines trained and validated on different datasets.…
This study evaluates publicly available deep-learning based lung segmentation models in transplant-eligible patients to determine their performance across disease severity levels, pathology categories, and lung sides, and to identify…
Colonoscopy is a standard imaging tool for visualizing the entire gastrointestinal (GI) tract of patients to capture lesion areas. However, it takes the clinicians excessive time to review a large number of images extracted from colonoscopy…
Purpose: The lung nodules localization in CT scan images is the most difficult task due to the complexity of the arbitrariness of shape, size, and texture of lung nodules. This is a challenge to be faced when coming to developing different…
Chest X-ray imaging is commonly used to diagnose pneumonia, but accurately localizing the pneumonia-affected regions typically requires detailed pixel-level annotations, which are costly and time consuming to obtain. To address this…
Lung cancer is the leading cause of cancer-related mortality in adults worldwide. Screening high-risk individuals with annual low-dose CT (LDCT) can support earlier detection and reduce deaths, but widespread implementation may strain the…
Lung cancer begins in the lungs and leading to the reason of cancer demise amid population in the creation. According to the American Cancer Society, which estimates about 27% of the deaths because of cancer. In the early phase of its…
Lung cancer risk estimation is gaining increasing importance as more countries introduce population-wide screening programs using low-dose CT (LDCT). As imaging volumes grow, scalable methods that can process entire lung volumes efficiently…
Lung cancer is one of the significant causes of cancer-related deaths globally. Early detection and treatment improve the chances of survival. Traditionally CT scans have been used to extract the most significant lung infection information…