AIMC Topic: Brain Neoplasms

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Clinical application of the RONNA G4 system - preliminary validation of 23 robotic frameless brain biopsies.

Croatian medical journal
AIMS: To report the outcomes of robot-assisted brain biopsies performed using a novel RONNA G4 system. The system was developed by a research group from the Faculty of Mechanical Engineering and Naval Architecture and a team of neurosurgeons from Dub...

3D brain glioma segmentation in MRI through integrating multiple densely connected 2D convolutional neural networks.

Journal of Zhejiang University. Science. B
To overcome the computational burden of processing three-dimensional (3D) medical scans and the lack of spatial information in two-dimensional (2D) medical scans, a novel segmentation method was proposed that integrates the segmentation results of th...

THE SAFETY AND EFFICACY OF ROBOT-ASSISTED STEREOTACTIC BIOPSY FOR BRAIN GLIOMA: EARLIEST INSTITUTIONAL EXPERIENCES AND EVALUATION OF LITERATURE.

Acta clinica Croatica
Robot-assisted brain tumor biopsy is becoming one of the most important innovative technologies in neurosurgical practice. The idea behind its engagement is to advance the safety and efficacy of the biopsy procedure, which is much in demand when plan...

Dual-responsive biohybrid neutrobots for active target delivery.

Science robotics
Swimming biohybrid microsized robots (e.g., bacteria- or sperm-driven microrobots) with self-propelling and navigating capabilities have become an exciting field of research, thanks to their controllable locomotion in hard-to-reach areas of the body ...

Brain metastasis detection using machine learning: a systematic review and meta-analysis.

Neuro-oncology
BACKGROUND: Accurate detection of brain metastasis (BM) is important for cancer patients. We aimed to systematically review the performance and quality of machine-learning-based BM detection on MRI in the relevant literature.

Fully automated hybrid approach to predict the IDH mutation status of gliomas via deep learning and radiomics.

Neuro-oncology
BACKGROUND: Glioma prognosis depends on isocitrate dehydrogenase (IDH) mutation status. We aimed to predict the IDH status of gliomas from preoperative MR images using a fully automated hybrid approach with convolutional neural networks (CNNs) and ra...

Evolution of Deep Learning Algorithms for MRI-Based Brain Tumor Image Segmentation.

Critical reviews in biomedical engineering
Brain tumor textures are among the most challenging features for neuroradiologists to extract from magnetic resonance images (MRIs). Exceptionally high-grade tumors such as gliomas require quick and precise diagnosis and medical intervention due to t...

Differentiating Small-Cell Lung Cancer From Non-Small-Cell Lung Cancer Brain Metastases Based on MRI Using Efficientnet and Transfer Learning Approach.

Technology in cancer research & treatment
Differentiation between small-cell lung cancer (SCLC) from non-small-cell lung cancer (NSCLC) brain metastases is crucial due to the different clinical behaviors of the two tumor types. We propose the use of a deep learning and transfer learning appr...

A Review on Deep Learning Architecture and Methods for MRI Brain Tumour Segmentation.

Current medical imaging
BACKGROUND: The automatic segmentation of brain tumour from MRI medical images is mainly covered in this review. Recently, state-of-the-art performance is provided by deep learning- based approaches in the field of image classification, segmentation,...

Intelligent medical image feature extraction method based on improved deep learning.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Medical patients can be diagnosed early, however it is difficult to extract effective features in medical image segmentation based on semantic information.