AIMC Topic: Tomography, X-Ray Computed

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Drawing insights from COVID-19-infected patients using CT scan images and machine learning techniques: a study on 200 patients.

Environmental science and pollution research international
As the whole world is witnessing what novel coronavirus (COVID-19) can do to the mankind, it presents several unique features also. In the absence of specific vaccine for COVID-19, it is essential to detect the disease at an early stage and isolate a...

DCT-MIL: Deep CNN transferred multiple instance learning for COPD identification using CT images.

Physics in medicine and biology
While many pre-defined computed tomographic (CT) measures have been utilized to characterize chronic obstructive pulmonary disease (COPD), it is still challenging to represent pathological alternations of multiple dimensions and highly spatial hetero...

Radiogenomics for predicting p53 status, PD-L1 expression, and prognosis with machine learning in pancreatic cancer.

British journal of cancer
BACKGROUND: Radiogenomics is an emerging field that integrates "Radiomics" and "Genomics". In the current study, we aimed to predict the genetic information of pancreatic tumours in a simple, inexpensive, and non-invasive manner, using cancer imaging...

Deep learning vs. atlas-based models for fast auto-segmentation of the masticatory muscles on head and neck CT images.

Radiation oncology (London, England)
BACKGROUND: Impaired function of masticatory muscles will lead to trismus. Routine delineation of these muscles during planning may improve dose tracking and facilitate dose reduction resulting in decreased radiation-related trismus. This study aimed...

Reinventing radiation therapy with machine learning and imaging bio-markers (radiomics): State-of-the-art, challenges and perspectives.

Methods (San Diego, Calif.)
Radiation therapy is a pivotal cancer treatment that has significantly progressed over the last decade due to numerous technological breakthroughs. Imaging is now playing a critical role on deployment of the clinical workflow, both for treatment plan...

Time-distanced gates in long short-term memory networks.

Medical image analysis
The Long Short-Term Memory (LSTM) network is widely used in modeling sequential observations in fields ranging from natural language processing to medical imaging. The LSTM has shown promise for interpreting computed tomography (CT) in lung screening...

Implementation of a Deep Learning-Based Computer-Aided Detection System for the Interpretation of Chest Radiographs in Patients Suspected for COVID-19.

Korean journal of radiology
OBJECTIVE: To describe the experience of implementing a deep learning-based computer-aided detection (CAD) system for the interpretation of chest X-ray radiographs (CXR) of suspected coronavirus disease (COVID-19) patients and investigate the diagnos...