AIMC Topic: Radiometry

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Automated robotic-assisted patient positioning method and dosimetric impact analysis for boron neutron capture therapy.

Scientific reports
Boron Neutron Capture Therapy (BNCT) represents a revolutionary approach in targeted radiation treatment for cancer. While the therapy's potential in precise targeting is well-recognized, a critical bottleneck remains in the accurate positioning of p...

Future Perspectives of Artificial Intelligence in Bone Marrow Dosimetry and Individualized Radioligand Therapy.

Seminars in nuclear medicine
Radioligand therapy is an emerging and effective treatment option for various types of malignancies, but may be intricately linked to hematological side effects such as anemia, lymphopenia or thrombocytopenia. The safety and efficacy of novel therano...

The role of biomarkers and dosimetry parameters in overall and progression free survival prediction for patients treated with personalized Y glass microspheres SIRT: a preliminary machine learning study.

European journal of nuclear medicine and molecular imaging
BACKGROUND: Overall Survival (OS) and Progression-Free Survival (PFS) analyses are crucial metrics for evaluating the efficacy and impact of treatment. This study evaluated the role of clinical biomarkers and dosimetry parameters on survival outcomes...

Is deep learning-enabled real-time personalized CT dosimetry feasible using only patient images as input?

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: To propose a novel deep-learning based dosimetry method that allows quick and accurate estimation of organ doses for individual patients, using only their computed tomography (CT) images as input.

Enhancing voxel-based dosimetry accuracy with an unsupervised deep learning approach for hybrid medical image registration.

Medical physics
BACKGROUND: Deformable registration is required to generate a time-integrated activity (TIA) map which is essential for voxel-based dosimetry. The conventional iterative registration algorithm using anatomical images (e.g., computed tomography (CT)) ...

Novel dosimetric validation of a commercial CT scanner based deep learning automated contour solution for prostate radiotherapy.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: OAR delineation accuracy influences: (i) a patient's optimised dose distribution (PD), (ii) the reported doses (RD) presented at approval, which represent plan quality. This study utilised a novel dosimetric validation methodology, comprehen...

Dosimetric impact of contour editing on CT and MRI deep-learning autosegmentation for brain OARs.

Journal of applied clinical medical physics
PURPOSE: To establish the clinical applicability of deep-learning organ-at-risk autocontouring models (DL-AC) for brain radiotherapy. The dosimetric impact of contour editing, prior to model training, on performance was evaluated for both CT and MRI-...

An artificial neural network based approach for predicting the proton beam spot dosimetric characteristics of a pencil beam scanning technique.

Biomedical physics & engineering express
Utilising Machine Learning (ML) models to predict dosimetric parameters in pencil beam scanning proton therapy presents a promising and practical approach. The study developed Artificial Neural Network (ANN) models to predict proton beam spot size an...

Organ dose prediction for patients undergoing radiotherapy CBCT chest examinations using artificial intelligence.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: To propose an artificial intelligence (AI)-based method for personalized and real-time dosimetry for chest CBCT acquisitions.