Search Results - "Puzhakkal, Niyas"

Self-supervised approach for organs at risk segmentation of abdominal CT images by Francis, Seenia, Minino, Coutinho Austin, P N, Pournami, Puzhakkal, Niyas, P B, Jayaraj

“…Accurate segmentation of organs at risk is essential for radiation therapy planning. However, manual segmentation is time-consuming and prone to inter and…”
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Effect of fluence smoothing on the quality of intensity-modulated radiation treatment plans by Niyas, Puzhakkal, Abdullah, Kallikuzhiyil Kochunny, Noufal, Manthala Padannayil, Sankaran Nair, Thekkedath

“…A fluence-smoothing function applied for reducing the complexity of a treatment plan is an optional requirement in the inverse planning optimization algorithm…”
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Development and validation of 3D printed anthropomorphic head phantom with eccentric holes for medical LINAC quality assurance testing in stereotactic radiosurgery by A K, Shahi Nabhan, Saxena, Kritik, Puzhakkal, Niyas, Mathew, Jose, K, Deepak Lawrence

“…•Design and development of 3 D printed, water filled generic anthropomorphic head phantom for Stereotactic radiosurgery.•Hydrostatic failure analysis of…”
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ContourGAN: Auto‐contouring of organs at risk in abdomen computed tomography images using generative adversarial network by Francis, Seenia, Jayaraj, P. B., Pournami, P. N., Puzhakkal, Niyas

“…Accurately identifying and contouring the organs at risk (OARs) is a crucial step in radiation treatment planning for precise dose calculation. This task…”
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MemU-Net: A new volumetric dose prediction model using deep learning techniques in radiation treatment planning by Chandran, Lekshmy P., K.A., Abdul Nazeer, Puzhakkal, Niyas, Makuny, Dinesh

“…Automatic radiation treatment planning systems are gaining significance nowadays. This paper presents a novel deep learning architecture for automatically…”
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A 3D U‐Net based two stage deep learning framework for predicting dose distributions in radiation treatment planning by Chandran, Lekshmy P., Kochannan Parampil Abdul Rahiman, Abdul Nazeer, Puzhakkal, Niyas, Makuni, Dinesh

“…Automation of the various steps of radiotherapy is gaining importance nowadays. Predicting the amount of radiation dose received by the tumor and nearby organs…”
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Design and development of additivemanufactured multi-channel brachytherapy applicators for cancer treatment by A. K., Shahi Nabhan, Saxena, Kritik, Puzhakkal, Niyas, Makuny, Dinesh, Mathew, Jose, Lawrence K., Deepak

“…Additive manufacturing (AM) is emerging as an effective manufacturing technology that benefits the medical field with its ease of quickly realizing complex…”
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Cone beam computed tomography enhancement using feature‐embedded variational autoencoder with a perceptual loss function by Joseph, Jiffy, Singh, Aparajit, P. N., Pournami, P. B., Jayaraj, Puzhakkal, Niyas

“…Image‐Guided Radiation Therapy (IGRT) is a cancer treatment method. IGRT usually follows a fragmented treatment track. The weight loss of a patient causes the…”
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SABOS‐Net: Self‐supervised attention based network for automatic organ segmentation of head and neck CT images by Francis, Seenia, Pooloth, Goutham, Singam, Sai Bala Subrahmanyam, Puzhakkal, Niyas, Pulinthanathu Narayanan, Pournami, Pottekkattuvalappil Balakrishnan, Jayaraj

“…The segmentation of Organs At Risk (OAR) in Computed Tomography (CT) images is an essential part of the planning phase of radiation treatment to avoid the…”
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Computed tomography image generation from magnetic resonance imaging using Wasserstein metric for MR‐only radiation therapy by Joseph, Jiffy, Hemanth, Challa, Pulinthanathu Narayanan, Pournami, Pottekkattuvalappil Balakrishnan, Jayaraj, Puzhakkal, Niyas

“…Magnetic resonance imaging (MRI) and computed tomography (CT) are the prevalent imaging techniques used in treatment planning in radiation therapy. Since…”
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Fan beam CT image synthesis from cone beam CT image using nested residual UNet based conditional generative adversarial network by Joseph, Jiffy, Biji, Ivan, Babu, Naveen, Pournami, P N, Jayaraj, P B, Puzhakkal, Niyas, Sabu, Christy, Patel, Vedkumar

“…A radiotherapy technique called Image-Guided Radiation Therapy adopts frequent imaging throughout a treatment session. Fan Beam Computed Tomography (FBCT)…”
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ThoraxNet: a 3D U-Net based two-stage framework for OAR segmentation on thoracic CT images by Francis, Seenia, Jayaraj, P B, Pournami, P N, Thomas, Manu, Jose, Ajay Thoomkuzhy, Binu, Allen John, Puzhakkal, Niyas

“…An important phase of radiation treatment planning is the accurate contouring of the organs at risk (OAR), which is necessary for the dose distribution…”
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Mean parotid dose prediction model using machine learning regression method for intensity-modulated radiotherapy in head and neck cancer by Ranjith, CP, puzhakkal, Niyas, Arunkrishnan, MP, Vysakh, R, Irfad, MP, Vijayagopal, KS, Jayashanker, S

“…Parotids are considered one of the major organs at risk in Head and Neck (HN) intensity-modulated radiotherapy (IMRT). Achieving proper target coverage with…”
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Validation of Dolphin dosimetry in three dimensional patient-specific quality assurance programme by Puzhakkal, Niyas, Kochunny, Abdullah Kallikuzhiyil, Makuny, Dinesh, Krishnan M.P, Arun, Poyil, Ranjith C., Raveendran, Vysakh

“…The aim of this study is to commission and validate Dolphin-Compass dosimetry as a patient-specific Quality Assurance (QA) device. The advancement of radiation…”
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Monte Carlo Simulation of Linear Accelerator for Dosimetry Analysis by Francis, Seenia, Suresh, Darshana, Nath, Shalini, Lakshmi D R, Saai, P B, Jayaraj, Puzhakkal, Niyas, P N, Pournami

“…Radiation therapy is a means to treat cancer that makes use of beams of intense energy to kill cells that are cancerous in nature. The equipment most often…”
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