BACKGROUND: Chordomas are locally invasive slow-growing tumors that are difficult to study because of the rarity of the tumors and the lack of significant volumes of patients with longitudinal follow-up. As such, there are currently no machine learni...
Clinical cancer research : an official journal of the American Association for Cancer Research
Jul 24, 2018
Current tumor-node-metastasis (TNM) staging system cannot provide adequate information for prediction of prognosis and chemotherapeutic benefits. We constructed a classifier to predict prognosis and identify a subset of patients who can benefit from...
PURPOSE: Manual contouring of gross tumor volumes (GTV) is a crucial and time-consuming process in rectum cancer radiotherapy. This study aims to develop a simple deep learning-based autosegmentation algorithm to segment rectal tumors on T2-weighted ...
International journal of radiation oncology, biology, physics
Feb 7, 2018
PURPOSE: Automating and standardizing the contouring of clinical target volumes (CTVs) can reduce interphysician variability, which is one of the largest sources of uncertainty in head and neck radiation therapy. In addition to using uniform margin e...
BACKGROUND: Tumor volume in head and neck squamous cell carcinoma (HNSCC) was mainly measured in nonsurgically treated patients. We analyzed the influence of tumor volume on complete response (CR), overall survival (OS), and clear surgical margins al...
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Dec 6, 2017
BACKGROUND AND PURPOSE: The gross tumour volume (GTV) is predictive of clinical outcome and consequently features in many machine-learned models. 4D-planning, however, has prompted substitution of the GTV with the internal gross target volume (iGTV)....
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)
Sep 23, 2017
The aim of this study was to investigate the impact of pixel-based machine learning (ML) techniques, i.e., fuzzy-c-means clustering method (FCM), and the artificial neural network (ANN) and support vector machine (SVM), on an automated framework for ...
International journal of radiation oncology, biology, physics
Nov 27, 2016
PURPOSE: Although the metric precision of robotic stereotactic body radiation therapy in the presence of breathing motion is widely known, we investigated the dosimetric implications of breathing phase-related residual tracking errors.
We have proposed a computer-assisted framework for machine-learning-based delineation of gross tumor volumes (GTVs) following an optimum contour selection (OCS) method. The key idea of the proposed framework was to feed image features around GTV cont...
PURPOSE: To compare diameter as a continuous variable with categorical R.E.N.A.L. nephrometry score (RNS) in predicting surgical outcomes of robotic partial nephrectomy (RPN).
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