Oncology/Hematology

Brain Cancer

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

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REPAIR: Reciprocal assistance imputation-representation learning for glioma diagnosis with incomplete MRI sequences.

The absence of MRI sequences is a common occurrence in clinical practice, posing a significant chall...

Radiation and contrast dose reduction in coronary CT angiography for slender patients with 70 kV tube voltage and deep learning image reconstruction.

OBJECTIVE: To evaluate the radiation and contrast dose reduction potential of combining 70 kV with d...

RAPTOR-AI: An open-source AI powered radiation protection toolkit for radioisotopes.

Artificial intelligence (AI) has gained significant attention in various scientific fields due to it...

[Advances in low-dose cone-beam computed tomography image reconstruction methods based on deep learning].

Cone-beam computed tomography (CBCT) is widely used in dentistry, surgery, radiotherapy and other me...

Validation and Derivation of miRNA-Based Germline Signatures Predicting Radiation Toxicity in Prostate Cancer.

PURPOSE: Although radiotherapy (RT) is one of the primary treatment modalities used in the treatment...

Future Applications of Cardiothoracic CT.

Radiologists are witnessing astonishing innovation and advancement of CT technologies and their clin...

Dimensional Synthesis of 6-DOF Parallel Robot for Intra-Operative Radiation Therapy.

BACKGROUND: In order to meet the kinematic requirements of large range of motion, payload, and stiff...

Deep learning driven interpretable and informed decision making model for brain tumour prediction using explainable AI.

Brain Tumours are highly complex, particularly when it comes to their initial and accurate diagnosis...

Automated field-in-field planning for tangential breast radiation therapy based on digitally reconstructed radiograph.

BACKGROUND: The tangential field-in-field (FIF) technique is a widely used method in breast radiatio...

Real-time brain tumour diagnoses using a novel lightweight deep learning model.

Brain tumours continue to be a primary cause of worldwide death, highlighting the critical need for ...

Deep learning-based triple-tracer brain PET scanning in a single session: A simulation study using clinical data.

OBJECTIVES: Multiplexed Positron Emission Tomography (PET) imaging allows simultaneous acquisition o...

Driving Knowledge to Action: Building a Better Future With Artificial Intelligence-Enabled Multidisciplinary Oncology.

Artificial intelligence (AI) is transforming multidisciplinary oncology at an unprecedented pace, re...

Prediction methodology of air absorbed dose rates for Chinese cities with deep learning models.

Air absorbed dose rate is a key indicator of environmental radiation exposure. In China, automated e...

Radiation oncology patients' perceptions of artificial intelligence and machine learning in cancer care: A multi-centre cross-sectional study.

AIM: The use of artificial intelligence (AI) and machine learning (ML) is increasingly widespread in...

Wrist and elbow fracture detection and segmentation by artificial intelligence using point-of-care ultrasound.

PURPOSE: Distal radius (wrist) and supracondylar (elbow) fractures are common in children presenting...

Multi-class brain malignant tumor diagnosis in magnetic resonance imaging using convolutional neural networks.

Glioblastoma (GBM), primary central nervous system lymphoma (PCNSL), and brain metastases (BM) are c...

Ultra-Sparse-View Cone-Beam CT Reconstruction-Based Strictly Structure-Preserved Deep Neural Network in Image-Guided Radiation Therapy.

Radiation therapy is regarded as the mainstay treatment for cancer in clinic. Kilovoltage cone-beam ...

Hierarchically Optimized Multiple Instance Learning With Multi-Magnification Pathological Images for Cerebral Tumor Diagnosis.

Accurate diagnosis of cerebral tumors is crucial for effective clinical therapeutics and prognosis. ...

Deep learning-driven modality imputation and subregion segmentation to enhance high-grade glioma grading.

PURPOSE: This study aims to develop a deep learning framework that leverages modality imputation and...

Harnessing artificial intelligence to address immune response heterogeneity in low-dose radiation therapy.

Low-dose radiation therapy has emerged as a promising modality for cancer treatment because of its a...

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