Correction: Brochet et al. A Quantitative Comparison between Shannon and Tsallis-Havrda-Charvat Entropies Applied to Cancer Outcome Prediction. 2022, , 436.

Alexandre Huat, Sébastien Thureau, David Pasquier, Isabelle Gardin, Romain Modzelewski, David Gibon, Juliette Thariat and Vincent Grégoire were not included as authors in the original publication [...

A Quantitative Comparison between Shannon and Tsallis-Havrda-Charvat Entropies Applied to Cancer Outcome Prediction.

In this paper, we propose to quantitatively compare loss functions based on parameterized Tsallis-Havrda-Charvat entropy and classical Shannon entropy for the training of a deep network in the case of small datasets which are usually encountered in medical applications. Shannon cross-entropy is widely used as a loss function for most neural networks applied to the segmentation, classification and detection of images. Shannon entropy is a particular case of Tsallis-Havrda-Charvat entropy.

Inter-clinician variability in making dosimetric decisions in pediatric treatment: a balance between efficacy and late effects.

Purpose: To investigate variability of clinical target volume (CTV) delineation and deviations according to doses delivered in normal tissue for abdominal tumor irradiation in children.

Material And Methods: For a case of nephroblastoma six French pediatric radiation oncologists outlined post-operative CTV, on the same dosimetric CT scan according to the International Society for Pediatric Oncology 2001 protocol. On a reference CTV and organs at risk (OAR), we performed dosimetric planning with the constraints as 25.

MRI definition of target volumes using fuzzy logic method for three-dimensional conformal radiation therapy.

Purpose: Three-dimensional (3D) volume determination is one of the most important problems in conformal radiation therapy. Techniques of volume determination from tomographic medical imaging are usually based on two-dimensional (2D) contour definition with the result dependent on the segmentation method used, as well as on the user's manual procedure. The goal of this work is to describe and evaluate a new method that reduces the inaccuracies generally observed in the 2D contour definition and 3D volume reconstruction process.