AIMC Topic: Tomography, X-Ray Computed

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Use of CT and artificial intelligence in suspected or COVID-19 positive patients: statement of the Italian Society of Medical and Interventional Radiology.

La Radiologia medica
The COVID-19 pandemic started in Italy in February 2020 with an exponential growth that has exceeded the number of cases reported in China. Italian radiology departments found themselves at the forefront in the management of suspected and positive CO...

Classification of COVID-19 patients from chest CT images using multi-objective differential evolution-based convolutional neural networks.

European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology
Early classification of 2019 novel coronavirus disease (COVID-19) is essential for disease cure and control. Compared with reverse-transcription polymerase chain reaction (RT-PCR), chest computed tomography (CT) imaging may be a significantly more tr...

Comparison of deep learning models for natural language processing-based classification of non-English head CT reports.

Neuroradiology
PURPOSE: Natural language processing (NLP) can be used for automatic flagging of radiology reports. We assessed deep learning models for classifying non-English head CT reports.

A cross-modal 3D deep learning for accurate lymph node metastasis prediction in clinical stage T1 lung adenocarcinoma.

Lung cancer (Amsterdam, Netherlands)
OBJECTIVES: The evaluation of lymph node (LN) status by radiologists based on preoperative computed tomography (CT) lacks high precision for early lung cancer patients; erroneous evaluations result in inappropriate therapeutic plans and increase the ...

Preoperative assessment of lymph node metastasis in Colon Cancer patients using machine learning: a pilot study.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: Preoperative detection of lymph node (LN) metastasis is critical for planning treatments in colon cancer (CC). The clinical diagnostic criteria based on the size of the LNs are not sensitive to determine metastasis using CT images. In thi...

Learning-based local-to-global landmark annotation for automatic 3D cephalometry.

Physics in medicine and biology
The annotation of three-dimensional (3D) cephalometric landmarks in 3D computerized tomography (CT) has become an essential part of cephalometric analysis, which is used for diagnosis, surgical planning, and treatment evaluation. The automation of 3D...

Deep learning-based liver segmentation for fusion-guided intervention.

International journal of computer assisted radiology and surgery
PURPOSE: Tumors often have different imaging properties, and there is no single imaging modality that can visualize all tumors. In CT-guided needle placement procedures, image fusion (e.g. with MRI, PET, or contrast CT) is often used as image guidanc...