Related papers: Development and Characterization of a Chest CT Atl…
Cancer diagnosis, prognosis, and therapeutic response prediction are heavily influenced by the relationship between the histopathological structures and the function of the tissue. Recent approaches acknowledging the structure-function…
The goal of this study is to assess the feasibility of airway geometry as a biomarker for ASD. Chest CT images of children with a documented diagnosis of ASD as well as healthy controls were identified retrospectively. 54 scans were…
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…
Using fiducial markers on patient's body surface to predict the tumor location is a widely used approach in lung cancer radiotherapy. The purpose of this work is to propose an algorithm that automatically identifies a sparse set of…
The processing and analysis of computed tomography (CT) imaging is important for both basic scientific development and clinical applications. In AutoCT, we provide a comprehensive pipeline that integrates an end-to-end automatic…
Lung cancer is the number one cause of cancer deaths. Many early stage lung cancer patients have resectable tumors; however, their cardiopulmonary function needs to be properly evaluated before they are deemed operative candidates.…
Uterine leiomyosarcoma (LMS) is a rare but aggressive malignancy. On imaging, it is difficult to differentiate LMS from, for example, degenerated leiomyoma (LM), a prevalent but benign condition. We curated a data set of 115 axial…
Imaging exams, such as chest radiography, will yield a small set of common findings and a much larger set of uncommon findings. While a trained radiologist can learn the visual presentation of rare conditions by studying a few…
Body tissue composition is a long-known biomarker with high diagnostic and prognostic value in cardiovascular, oncological and orthopaedic diseases, but also in rehabilitation medicine or drug dosage. In this study, the aim was to develop a…
At present, the incidence and fatality rate of lung cancer in China rank first among all malignant tumors. Despite the continuous development and improvement of China's medical level, the overall 5-year survival rate of lung cancer patients…
Total lung volume is an important quantitative biomarker and is used for the assessment of restrictive lung diseases. In this study, we investigate the performance of several deep-learning approaches for automated measurement of total lung…
The field of lung nodule detection and cancer prediction has been rapidly developing with the support of large public data archives. Previous studies have largely focused on cross-sectional (single) CT data. Herein, we consider longitudinal…
Body composition assessment using CT images can potentially be used for a number of clinical applications, including the prognostication of cardiovascular outcomes, evaluation of metabolic health, monitoring of disease progression,…
We present a fully automated method for top-down segmentation of the pulmonary arterial tree in low-dose thoracic CT images. The main basal pulmonary arteries are identified near the lung hilum by searching for candidate vessels adjacent to…
Non-invasive radiological-based lesion characterization and identification, e.g., to differentiate cancer subtypes, has long been a major aim to enhance oncological diagnosis and treatment procedures. Here we study a specific population of…
Gastric cancer is one of the most common cancers, which ranks third among the leading causes of cancer death. Biopsy of gastric mucosa is a standard procedure in gastric cancer screening test. However, manual pathological inspection is…
A computer-aided detection (CAD) system for the identification of pulmonary nodules in low-dose multi-detector helical Computed Tomography (CT) images was developed in the framework of the MAGIC-5 Italian project. One of the main goals of…
This work introduces a new latent diffusion model to generate high-quality 3D chest CT scans conditioned on 3D anatomical masks. The method synthesizes volumetric images of size 256x256x256 at 1 mm isotropic resolution using a single…
Laryngeal cancer imaging research lacks standardised datasets to enable reproducible deep learning (DL) model development. We present LaryngealCT, a curated benchmark of 1,029 computed tomography (CT) scans aggregated from six collections…
In recent years, electronic nose devices have become a popular approach for identifying respiratory disorders including lung cancer. Traditional e-nose systems have had very consistent principles and patterns of sensor responses. After…