Gregory C. Sharp

What is he best known for?

The fields of study he is best known for:

• Artificial intelligence
• Statistics
• Computer vision

Gregory C. Sharp focuses on Artificial intelligence, Image registration, Computer vision, Nuclear medicine and Medical imaging. His research in Artificial intelligence intersects with topics in Linear combination and Pattern recognition. His work in Image registration tackles topics such as Iterative method which are related to areas like Odometry, Mobile robot and Feature extraction.

His work on Computer vision deals in particular with Image processing and Iterative reconstruction. His work deals with themes such as Dose fractionation, Radiology, Fiducial marker, Respiratory gating and Amplitude, which intersect with Nuclear medicine. The various areas that he examines in his Medical imaging study include Segmentation and Voxel.

His most cited work include:

• ICP registration using invariant features (480 citations)
• Evaluation of Registration Methods on Thoracic CT: The EMPIRE10 Challenge (330 citations)
• Prediction of respiratory tumour motion for real-time image-guided radiotherapy (320 citations)

What are the main themes of his work throughout his whole career to date?

Gregory C. Sharp mostly deals with Nuclear medicine, Artificial intelligence, Computer vision, Image registration and Medical imaging. The concepts of his Nuclear medicine study are interwoven with issues in Radiation therapy, Radiation treatment planning, Radiology and Proton therapy. His biological study spans a wide range of topics, including Position and Pattern recognition.

As part of his studies on Computer vision, Gregory C. Sharp often connects relevant subjects like Image-guided radiation therapy. Gregory C. Sharp combines subjects such as Metric, Histogram, Computed tomography, Ground truth and Algorithm with his study of Image registration. His studies deal with areas such as Image resolution, Cone beam computed tomography and Radiography as well as Medical imaging.

He most often published in these fields:

• Nuclear medicine (40.99%)
• Artificial intelligence (36.96%)
• Computer vision (27.64%)

What were the highlights of his more recent work (between 2016-2021)?

• Nuclear medicine (40.99%)
• Proton therapy (18.32%)
• Artificial intelligence (36.96%)

In recent papers he was focusing on the following fields of study:

Gregory C. Sharp mainly focuses on Nuclear medicine, Proton therapy, Artificial intelligence, Radiation therapy and Imaging phantom. His Nuclear medicine research incorporates elements of Image registration and Volume. Gregory C. Sharp works mostly in the field of Image registration, limiting it down to topics relating to Image resolution and, in certain cases, Function, as a part of the same area of interest.

His Artificial intelligence research is multidisciplinary, incorporating elements of External beam radiotherapy, Key, Computer vision and Pattern recognition. His Computer vision study combines topics in areas such as Image-guided radiation therapy and Vertebra. His Radiation therapy research entails a greater understanding of Radiology.

Between 2016 and 2021, his most popular works were:

• Evaluation of segmentation methods on head and neck CT: Auto-segmentation challenge 2015 (101 citations)
• Why rankings of biomedical image analysis competitions should be interpreted with care (87 citations)
• Autosegmentation for thoracic radiation treatment planning: A grand challenge at AAPM 2017. (68 citations)

In his most recent research, the most cited papers focused on:

• Artificial intelligence
• Statistics
• Radiation therapy

His primary areas of investigation include Proton therapy, Nuclear medicine, Segmentation, Data science and Best practice. His Proton therapy research is multidisciplinary, incorporating perspectives in Scatter correction, Intensity, Tomography and Monte Carlo method. His research investigates the link between Tomography and topics such as Prostate that cross with problems in Radiation therapy.

His Nuclear medicine research is mostly focused on the topic Imaging phantom. Research on Artificial intelligence and Pattern recognition is a part of his Segmentation study. The Artificial intelligence study combines topics in areas such as Atlas and Atlas.