ArticleCancers2023
deepPERFECT: Novel Deep Learning CT Synthesis Method for Expeditious Pancreatic Cancer Radiotherapy.
Article in Cancers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
14 citing papers in PubMed.
- Artificial intelligence in pancreatic cancer: applications in early detection, tumor staging, and survival prediction-a comprehensive review.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Review
- Deep Learning for CT Synthesis in Radiotherapy.Bioengineering (Basel, Switzerland) · 2025Review
- Simulation-free workflow for lattice radiation therapy using deep learning predicted synthetic computed tomography: A feasibility study.Journal of applied clinical medical physics · 2025Article
- Enhancing pancreatic cancer detection in CT images through secretary wolf bird optimization and deep learning.Scientific reports · 2025Article
- Article
- EXACT-Net: Framework for EHR-Guided Lung Tumor Auto-Segmentation for Non-Small Cell Lung Cancer Radiotherapy.Cancers · 2024Article
- Simulation-free magnetic resonance-guided radiation therapy of prostate cancer.Physics and imaging in radiation oncology · 2024Article
- Artificial Intelligence in Pancreatic Image Analysis: A Review.Sensors (Basel, Switzerland) · 2024Review
- Deep Learning Applications in Pancreatic Cancer.Cancers · 2024Review
- Clinical applications of generative artificial intelligence in radiology: image translation, synthesis, and text generation.BJR artificial intelligence · 2024Review
- Article
- Ultrasound Imaging with Flexible Array Transducer for Pancreatic Cancer Radiation Therapy.Cancers · 2023Article
- Surgical Instrument Detection Algorithm Based on Improved YOLOv7x.Sensors (Basel, Switzerland) · 2023Article
- DAART: a deep learning platform for deeply accelerated adaptive radiation therapy for lung cancer.Frontiers in oncology · 2023Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Major sources of delay in the standard of care RT workflow are the need for multiple appointments and separate image acquisition. In this work, we addressed the question of how we can expedite the workflow by synthesizing planning CT from diagnostic CT. This idea is based on the theory that diagnostic CT can be used for RT planning, but in practice, due to the differences in patient setup and acquisition techniques, separate planning CT is required. We developed a generative deep learning model, deepPERFECT, that is trained to capture these differences and generate deformation vector fields to transform diagnostic CT into preliminary planning CT. We performed detailed analysis both from an image quality and a dosimetric point of view, and showed that deepPERFECT enabled the preliminary RT planning to be used for preliminary and early plan dosimetric assessment and evaluation.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.