AIMC Topic: Tomography, X-Ray Computed

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Scout-Dose-TCM: direct and prospective scout-based estimation of personalized organ and effective doses from tube current modulated CT exams.

Physics in medicine and biology
This study proposes Scout-Dose-TCM for direct, prospective estimation of organ-level and effective doses under tube current modulation (TCM) and compares its performance with two established methods.Contrast-enhanced chest-abdomen-pelvis CT exams fro...

Investigation of data-driven stopping power calibration of treatment planning x-ray CT from simulated sparse-view proton radiographies.

Physics in medicine and biology
Proton therapy treatment planning currently needs to account for relatively large range uncertainty margins primarily due to the semi-empirical calibration of the treatment planning x-ray computed tomography (CT) to proton stopping power relative to ...

Automatic detection of urinary stones from non-contrast enhanced computed tomography images.

Urolithiasis
Urinary stones, one of the most common emergency conditions, traverse the ureter, urine flow is obstructed, resulting in hydronephrosis and severe pain. However, vessel wall calcifications or phleboliths are frequently observed in abdominal and pelvi...

MR-based synthetic CT generation using dual-attention enhanced 3D Conditional GAN for head and neck radiotherapy.

Biomedical physics & engineering express
. This study aims to synthesize CT from MR images for radiotherapy planning of head and neck tumor using an improved three-dimensional conditional generative adversarial network (3D cGAN) based on dual-attention modules.. A total of 212 paired CT and...

FBFormer: interventional ultra-sparse CT reconstruction with image prior using feature back-projection and transformer.

Physics in medicine and biology
. CT-guided interventional procedures hold a significant position in clinical practice. However, due to the high number of scans and prolonged procedure times, patients are exposed to considerable radiation doses. This study aims to utilize intraoper...

Foundation model based prediction of lung cancer survival using temporal changes in dual time point CT scans.

Scientific reports
Lung cancer remains a significant cause of mortality, with non-small cell lung cancer (NSCLC) representing most cases. Currently, clinical data based models fall short in predicting survival while more advanced deep learning based image models requir...

Hybrid radiomic-HOG ensemble model for accurate pulmonary nodule diagnosis.

Biomedical physics & engineering express
Lung cancer remains one of the deadliest forms of cancer worldwide, making early and accurate pulmonary-nodule classification essential for improving patient prognosis. This study presents a robust ensemble-stacking framework that integrates Histogra...

Prediction of recurrence after resection in hepatocellular carcinoma via whole liver deep learning on preoperative contrast-enhanced CT.

Scientific reports
This study aimed to develop a fully automated survival prediction (FASP) system that analyzes whole-liver regions from preoperative contrast-enhanced CT scans for predicting recurrence-free survival (RFS) after curative resection in Hepatocellular ca...

Computed tomography-based nnU-Net for region-specific brain structural changes across the alzheimer's continuum and frontotemporal dementia subtypes.

Scientific reports
Quantifying structural brain changes is critical for diagnosing and monitoring neurodegenerative diseases. Although magnetic resonance imaging (MRI) is the silver standard, limited accessibility and cost hamper routine use. We developed a deep learni...

An interpretable machine learning approach to prognosis of melioidosis pneumonia via computed tomography quantification and clinical data.

Scientific reports
This study aimed to develop a dataset comprising computed tomography (CT) images and clinical data for melioidosis pneumonia and to utilize machine learning for assisting in prognosis prediction of the disease. We retrospectively analyzed multicenter...