Oncology/Hematology

Brain Cancer

Latest AI and machine learning research in brain cancer for healthcare professionals.

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Image-based Classification of Tumor Type and Growth Rate using Machine Learning: a preclinical study.

Medical images such as magnetic resonance (MR) imaging provide valuable information for cancer detec...

DeepOrganNet: On-the-Fly Reconstruction and Visualization of 3D / 4D Lung Models from Single-View Projections by Deep Deformation Network.

This paper introduces a deep neural network based method, i.e., DeepOrganNet, to generate and visual...

Comparison of machine learning classifiers for differentiation of grade 1 from higher gradings in meningioma: A multicenter radiomics study.

BACKGROUND AND PURPOSE: Advanced imaging analysis for the prediction of tumor biology and modelling ...

Fully automatic catheter segmentation in MRI with 3D convolutional neural networks: application to MRI-guided gynecologic brachytherapy.

External-beam radiotherapy followed by high dose rate (HDR) brachytherapy is the standard-of-care fo...

Automated brain extraction of multisequence MRI using artificial neural networks.

Brain extraction is a critical preprocessing step in the analysis of neuroimaging studies conducted ...

Personalized oncology with artificial intelligence: The case of temozolomide.

PURPOSE: Using artificial intelligence techniques, we compute optimal personalized protocols for tem...

Machine learning applications in prostate cancer magnetic resonance imaging.

With this review, we aimed to provide a synopsis of recently proposed applications of machine learni...

Machine learning and glioma imaging biomarkers.

AIM: To review how machine learning (ML) is applied to imaging biomarkers in neuro-oncology, in part...

Use of artificial neural network for pretreatment verification of intensity modulation radiation therapy fields.

OBJECTIVE: The accuracy of dose delivery for intensity modulated radiotherapy (IMRT) treatments shou...

Radiomics Analysis for Glioma Malignancy Evaluation Using Diffusion Kurtosis and Tensor Imaging.

PURPOSE: A noninvasive diagnostic method to predict the degree of malignancy accurately would be of ...

MRI-based treatment planning for proton radiotherapy: dosimetric validation of a deep learning-based liver synthetic CT generation method.

Magnetic resonance imaging (MRI) has been widely used in combination with computed tomography (CT) r...

Incorporating imaging information from deep neural network layers into image guided radiation therapy (IGRT).

BACKGROUND AND PURPOSE: To investigate a novel markerless prostate localization strategy using a pre...

Deep learning derived tumor infiltration maps for personalized target definition in Glioblastoma radiotherapy.

PURPOSE: Glioblastoma is routinely treated by concomitant radiochemotherapy. Current target definiti...

Brain Tumour Segmentation Using Convolutional Neural Network with Tensor Flow.

Introduction: The determination of tumour extent is a major challenging task in brain tumour plannin...

Brain tumor classification using deep CNN features via transfer learning.

Brain tumor classification is an important problem in computer-aided diagnosis (CAD) for medical app...

A high-throughput screening and computation platform for identifying synthetic promoters with enhanced cell-state specificity (SPECS).

Cell state-specific promoters constitute essential tools for basic research and biotechnology becaus...

F-FDG-PET-based radiomics features to distinguish primary central nervous system lymphoma from glioblastoma.

The differential diagnosis of primary central nervous system lymphoma from glioblastoma multiforme (...

Clinical Documentation and Patient Care Using Artificial Intelligence in Radiation Oncology.

Detailed clinical documentation is required in the patient-facing specialty of radiation oncology. T...

Estimation of the radiation dose in pregnancy: an automated patient-specific model using convolutional neural networks.

OBJECTIVES: The conceptus dose during diagnostic imaging procedures for pregnant patients raises hea...

Automatic gas detection in prostate cancer patients during image-guided radiation therapy using a deep convolutional neural network.

PURPOSE: The detection of intestinal/rectal gas is very important during image-guided radiation ther...

Presurgical differentiation between malignant haemangiopericytoma and angiomatous meningioma by a radiomics approach based on texture analysis.

PURPOSE: To assess whether a machine-learning model based on texture analysis (TA) could yield a mor...

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