Lung cancer screening based on low-dose CT (LDCT) has now been widely applied because of its effectiveness and ease of performance. Radiologists who evaluate a large LDCT screening images face enormous challenges, including mechanical repetition and ...
BACKGROUND: Chest CT is used for the assessment of the severity of patients infected with novel coronavirus 2019 (COVID-19). We collected chest CT scans of 202 patients diagnosed with the COVID-19, and try to develop a rapid, accurate and automatic t...
Computer methods and programs in biomedicine
Aug 11, 2020
BACKGROUND AND OBJECTIVES: Writing diagnostic reports for medical images is a heavy and tedious work. The automatic generation of medical image diagnostic reports can assist doctors to reduce their workload and improve diagnosis efficiency. It is of ...
The conventional image segmentation techniques have a lot of issues with highest computational cost and low level accuracy for medical image diagnosis and genome analysis. The deep learning based optimization models utilize to predict the liver cance...
Fully-automated nuclear image segmentation is the prerequisite to ensure statistically significant, quantitative analyses of tissue preparations,applied in digital pathology or quantitative microscopy. The design of segmentation methods that work ind...
OBJECTIVE: Multi-frequency symmetry difference electrical impedance tomography (MFSD-EIT) can robustly detect and identify unilateral perturbations in symmetric scenes. Here, an investigation is performed to assess if the algorithm can be successfull...
Journal of applied clinical medical physics
Aug 10, 2020
PURPOSE: Segmentation of liver organ and tumors from computed tomography (CT) scans is an important task for hepatic surgical planning. Manual segmentation of liver and tumors is tedious, time-consuming, and biased to the clinician experience. Theref...
Robotic intravenous poles are automated supportive instrument that needs to be triggered by patients to hold medications and needed supplies. Healthcare engineering of robotic intravenous poles is advancing in order to improve the quality of health s...
Generative adversarial networks (GANs) and their extensions have carved open many exciting ways to tackle well known and challenging medical image analysis problems such as medical image de-noising, reconstruction, segmentation, data simulation, dete...
Nephroblastoma is the most common kidney tumour in children. Its diagnosis is based on imagery. In the SAIAD project, we have designed a platform for optimizing the segmentation of deformed kidney and tumour with a small dataset, using Artificial Int...
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