☆ 4.6 Review

Computational approaches for the reconstruction of optic nerve fibers along the visual pathway from medical images: a comprehensive review

FRONTIERS IN NEUROSCIENCE (2023)

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Article Biophysics

A unified global tractography framework for automatic visual pathway reconstruction

Jianzhong He et al.

Summary: The human visual pathway can be reconstructed noninvasively using diffusion MRI tractography. However, this process is challenging due to the complex fiber geometries and the skull base environment. In this paper, a unified global tractography framework is proposed to automatically reconstruct the visual pathway.

NMR IN BIOMEDICINE (2023)

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Article Computer Science, Artificial Intelligence

Superficial white matter analysis: An efficient point-cloud-based deep learning framework with supervised contrastive learning for consistent tractography parcellation across populations and dMRI acquisitions

Tengfei Xue et al.

Summary: Diffusion MRI tractography enables in vivo mapping of the brain's white matter connections. We propose a deep-learning-based framework, SupWMA, for efficient and consistent parcellation of superficial white matter (SWM) clusters from whole-brain tractography. SupWMA achieves highly consistent and accurate SWM parcellation results across different ages and health conditions, and it has a faster computational speed compared to other methods.

MEDICAL IMAGE ANALYSIS (2023)

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Article Computer Science, Artificial Intelligence

Fine Perceptive GANs for Brain MR Image Super-Resolution in Wavelet Domain

Senrong You et al.

Summary: Magnetic resonance (MR) imaging is crucial in clinical and brain exploration, yet it is challenging to acquire high-resolution MR images due to hardware limitations, scanning time, and cost. In this article, the authors propose FP-GANs, a model that uses divide-and-conquer approach to generate super-resolution MR images. The model separates and processes the low-frequency and high-frequency components of MR images and achieves better structure recovery and classification performance.

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS (2023)

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Article Computer Science, Interdisciplinary Applications

Bidirectional Mapping Generative Adversarial Networks for Brain MR to PET Synthesis

Shengye Hu et al.

Summary: This paper proposes a 3D end-to-end synthesis network called BMGAN for synthesizing PET images from brain MR images. The method utilizes a bidirectional mapping mechanism and employs a 3D Dense-UNet generator architecture and hybrid loss functions to generate high-quality cross-modality synthetic images while preserving the diverse brain structures of different subjects.

IEEE TRANSACTIONS ON MEDICAL IMAGING (2022)

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Article Radiology, Nuclear Medicine & Medical Imaging

General and custom deep learning autosegmentation models for organs in head and neck, abdomen, and male pelvis

Asma Amjad et al.

Summary: In this study, general and custom autosegmentation models were developed and evaluated for reducing workload and inconsistencies in organ segmentation for radiation treatment planning. The models, based on deep convolutional neural networks, achieved high accuracy using either diversified multi-institutional datasets or well-controlled single-institution datasets. Organ-based approaches were implemented to improve segmentation accuracy for small or complex organs. The autosegmentation models significantly reduced contouring time compared to manual contouring methods.

MEDICAL PHYSICS (2022)

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Article Computer Science, Artificial Intelligence

Multimodal medical image segmentation using multi-scale context- aware network

Xue Wang et al.

Summary: This paper proposes a multi-scale context-aware network (CA-Net) for multimodal medical image segmentation. The network captures rich context information with dense skip connection and assigns distinct weights to different channels. Extensive experiments demonstrate that the model achieves state-of-the-art performance on three benchmark datasets of different modalities.

NEUROCOMPUTING (2022)

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Article Clinical Neurology

Microstructural Visual Pathway White Matter Alterations in Primary Open-Angle Glaucoma: A Neurite Orientation Dispersion and Density Imaging Study

S. Haykal et al.

Summary: NODDI was used to characterize microstructural changes in the visual pathways of patients with primary open-angle glaucoma, revealing loss in both axonal coherence and density in the pregeniculate pathways and loss in axonal coherence only in the postgeniculate pathways.

AMERICAN JOURNAL OF NEURORADIOLOGY (2022)

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Article Radiology, Nuclear Medicine & Medical Imaging

Single-shell to multi-shell dMRI transformation using spatial and volumetric multilevel hierarchical reconstruction framework

Ranjeet Ranjan Jha et al.

Summary: Single or multi-shell high angular resolution diffusion imaging is an important technique for studying brain white matter fibers. The existing single-shell technique has limitations in estimating the intravoxel structure at the desired resolution. In this study, a deep learning architecture is proposed to reconstruct diffusion MRI volumes for different b-values using single-shell acquisitions, allowing for higher resolution and accurate fiber tracts. The proposed framework incorporates contextual information within each slice and across the slices to optimize network learning, achieving promising results in the validation.

MAGNETIC RESONANCE IMAGING (2022)

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Article Computer Science, Artificial Intelligence

Nerve optic segmentation in CT images using a deep learning model and a texture descriptor

Ramin Ranjbarzadeh et al.

Summary: This research aims to diagnose ICP quickly using a computer-aided diagnosis system. By employing methods such as image segmentation, image quality enhancement, and key information representation, the accurate detection of the nerve optic regions and calculation of its diameter were successfully achieved. Experimental results showed that compared to other methods, this approach can more accurately detect ICP, which can be used for early diagnosis and prevention of health problems in patients.

COMPLEX & INTELLIGENT SYSTEMS (2022)

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Article Radiology, Nuclear Medicine & Medical Imaging

VRfRNet: Volumetric ROI fODF reconstruction network for estimation of multi-tissue constrained spherical deconvolution with only single shell dMRI

Ranjeet Ranjan Jha et al.

Summary: Diffusion MRI (dMRI) is widely used for studying the brain structure, particularly the white matter region. The high angular resolution diffusion imaging (HARDI) technique is favored by researchers for its accurate estimation of fiber orientation. However, accurately estimating the intravoxel structure is challenging with the current single-shell HARDI. To address this issue, we propose a novel generative adversarial network, VRfRNet, for reconstructing multi-shell multi-tissue fiber orientation distribution function from single-shell HARDI volumes.

MAGNETIC RESONANCE IMAGING (2022)

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Article Computer Science, Artificial Intelligence

FOD-Net: A deep learning method for fiber orientation distribution angular super resolution

Rui Zeng et al.

Summary: Mapping the human connectome using fiber-tracking allows the study of brain connectivity. However, reliable connectome reconstruction using widely available clinical protocols remains challenging. This study introduces FOD-Net, a deep-learning-based framework that enhances the angular resolution of FOD images computed from clinical-quality dMRI data, enabling superior tractography and structural connectome reconstruction.

MEDICAL IMAGE ANALYSIS (2022)

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Article Neurosciences

Reproducible protocol to obtain and measure first-order relay human thalamic white-matter tracts

Mengxing Liu et al.

Summary: In this study, a reconstruction protocol based on in vivo diffusion MRI was developed to extract and measure specific axonal fiber tracts in individual first-order relay nuclei. The protocol demonstrated high computational and test-retest reproducibility. This new protocol is significant for both basic human brain neuroscience and clinical studies.

NEUROIMAGE (2022)

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Article Neurosciences

Deep learning-based parameter estimation in fetal diffusion-weighted MRI

Davood Karimi et al.

Summary: The study developed a novel methodology using deep learning techniques and newborn scan data to generate parameter estimation models for fetal DW-MRI, demonstrating significantly improved reconstruction accuracy, precision, and quality compared to standard estimation methods.

NEUROIMAGE (2021)

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Article Neurosciences

Learning to estimate the fiber orientation distribution function from diffusion-weighted MRI

Davood Karimi et al.

Summary: This study proposed a data-driven method to improve the accuracy and robustness of white matter fiber orientation distribution function (fODF) estimation, demonstrating effectiveness through training with simulated and real data. In phantom and real data experiments, the method showed higher accuracy compared to other competing methods, particularly in under sampled diffusion measurements. Additionally, expert ratings indicated significantly better reconstruction of various brain tracts using the proposed method.

NEUROIMAGE (2021)

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Article Optics

Semantic segmentation using deep learning to extract total extraocular muscles and optic nerve from orbital computed tomography images

Fubao Zhu et al.

Summary: A semantic segmentation method using a 3D neural network was developed to automatically extract total extraocular muscles (EOM) and optic nerve (ON) from orbital CT images, showing potential for clinical application in the diagnosis and prognosis of thyroid-associated ophthalmopathy (TAO).

OPTIK (2021)

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Article Neuroimaging

Lateral geniculate nucleus volume changes after optic neuritis in neuromyelitis optica: A longitudinal study

Athina Papadopoulou et al.

Summary: In patients with NMOSD, LGN volume is reduced after ON but does not change longitudinally in the absence of ON, suggesting no occult neurodegeneration of the afferent visual pathway in NMOSD.

NEUROIMAGE-CLINICAL (2021)

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Article Neurosciences

Deep Learning-Based Detection of Malformed Optic Chiasms From MRI Images

Robert J. Puzniak et al.

Summary: By training a CNN on T1w MRI images to segment optic chiasms, it can assist in diagnosing misroutings in patients with albinism. However, there is a significant difference in the quality of results between albino patients and the control group.

FRONTIERS IN NEUROSCIENCE (2021)

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Article Neurosciences

Comparison of multiple tractography methods for reconstruction of the retinogeniculate visual pathway using diffusion MRI

Jianzhong He et al.

Summary: This study compared four tractography methods and found that UKF-2T and iFOD1 produce the best results for RGVP reconstruction. The iFOD1 method can more accurately estimate the percentage of decussating fibers, while the UKF-2T method produces reconstructed RGVPs that better correspond to known anatomy.

HUMAN BRAIN MAPPING (2021)

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Article Multidisciplinary Sciences

CHIASM, the human brain albinism and achiasma MRI dataset

Robert J. Puzniak et al.

Summary: This project offers magnetic resonance imaging data from individuals with albinism and achiasma, which can serve as a platform for developing and validating tractography methods and exploring the characteristics of the human visual system in individuals with congenital abnormalities.

SCIENTIFIC DATA (2021)

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Article Computer Science, Artificial Intelligence

Track-to-Learn: A general framework for tractography with deep reinforcement learning

Antoine Theberge et al.

Summary: Diffusion MRI tractography is the only non-invasive tool to assess the white-matter structural connectivity of a brain. Using deep reinforcement learning to address tractography issues has shown competitive results and stable performance when generalizing to new data.

MEDICAL IMAGE ANALYSIS (2021)

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Article Neurosciences

Fully automated delineation of the optic radiation for surgical planning using clinically feasible sequences

Lee B. Reid et al.

Summary: This study introduces CONSULT, a technique that can automatically delineate the optic radiation through a combination of robust preprocessing, segmentation, and alignment stages, as well as simple improvements to standard tractography. CONSULT achieved error-free delineations in 99.4% of scans, with scan-rescan distance errors averaging 1 mm. Testing on participants with pathology showed successful and realistic delineations. This study demonstrates the ability to identify Meyer's Loop using clinically feasible sequences without requiring fundamental changes to tractography algorithms or complex post-processing methods.

HUMAN BRAIN MAPPING (2021)

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Article Clinical Neurology

Multiple sclerosis: structural and functional integrity of the visual system following alemtuzumab therapy

Chenyu Wang et al.

Summary: This study investigated the potential neuroprotective and pro-remyelinating effects of alemtuzumab in multiple sclerosis, using the visual pathway as a model. Results showed evidence of partial lesion remyelination after treatment, indicating a potential pro-reparative mechanism of action. The study provides insights for future MS remyelination trials and highlights the importance of studying function-structure specific effects of therapy in the visual system.

JOURNAL OF NEUROLOGY NEUROSURGERY AND PSYCHIATRY (2021)

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Article Radiology, Nuclear Medicine & Medical Imaging

SuperDTI: Ultrafast DTI and fiber tractography with deep learning

Hongyu Li et al.

Summary: The SuperDTI framework developed using deep learning is capable of generating fractional anisotropy, mean diffusivity maps, and fiber tractography from as few as six raw DWIs with a quantification error of less than 5% in all regions of interest. It demonstrates robustness to noises and motions in testing data and has the potential for clinical applications.

MAGNETIC RESONANCE IN MEDICINE (2021)

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Article Computer Science, Artificial Intelligence

A machine learning-based method for estimating the number and orientations of major fascicles in diffusion-weighted magnetic resonance imaging

Davood Karimi et al.

Summary: A machine learning-based technique is proposed for accurately estimating the number and orientations of fascicles in a voxel, outperforming classical and machine learning methods in predicting crossing fascicles and leading to more accurate tractography. This method also shows better robustness to measurement down sampling and expert quality assessment of tractography results compared to other methods.

MEDICAL IMAGE ANALYSIS (2021)

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Proceedings Paper Computer Science, Artificial Intelligence

Deep Fiber Clustering: Anatomically Informed Unsupervised Deep Learning for Fast and Effective White Matter Parcellation

Yuqian Chen et al.

Summary: The study introduces a novel WMFC framework based on unsupervised deep learning, solving the clustering problem as a self-supervised task and improving resistance to fiber point ordering. By incorporating anatomical segmentation data, the anatomical coherence of fiber clusters is further enhanced.

MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION - MICCAI 2021, PT VII (2021)

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Deep Attention Mask Regional Convolutional Neural Network for Head-and-Neck MRI Multi-Organ Auto-Delineation

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A Fully Automatic Method for Optic Radiation Tractography Applicable to Multiple Sclerosis Patients

Jean-Baptiste Davion et al.

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IEEE TRANSACTIONS ON MEDICAL IMAGING (2020)

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Microstructural Investigations of the Visual Pathways in Pediatric Epilepsy Neurosurgery: Insights From Multi-Shell Diffusion Magnetic Resonance Imaging

Luis M. Lacerda et al.

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Spatial probabilistic distribution map-based two-channel 3D U-net for visual pathway segmentation

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Diffusion MRI fiber tractography of the brain

Ben Jeurissen et al.

NMR IN BIOMEDICINE (2019)

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Overcoming Challenges of Cranial Nerve Tractography: A Targeted Review

Timothee Jacquesson et al.

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Haya Glick-Shames et al.

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Cognitive and White-Matter Compartment Models Reveal Selective Relations between Corticospinal Tract Microstructure and Simple Reaction Time

Esin Karahan et al.

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Shape constrained fully convolutional DenseNet with adversarial training for multiorgan segmentation on head and neck CT and low-field MR images

Nuo Tong et al.

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Differences between generalized Q-sampling imaging and diffusion tensor imaging in visualization of crossing neural fibers in the brain

Zhuoru Jin et al.

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Objective Detection of Eloquent Axonal Pathways to Minimize Postoperative Deficits in Pediatric Epilepsy Surgery Using Diffusion Tractography and Convolutional Neural Networks

Haotian Xu et al.

IEEE TRANSACTIONS ON MEDICAL IMAGING (2019)

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Assessment of optic nerve and optic tract alterations in patients with orbital space-occupying lesions using probabilistic diffusion tractography

Chun-Nan Wu et al.

INTERNATIONAL JOURNAL OF OPHTHALMOLOGY (2019)

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Aberrant visual pathway development in albinism: From retina to cortex

Sarim Ather et al.

HUMAN BRAIN MAPPING (2019)

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AnatomyNet: Deep learning for fast and fully automated whole-volume segmentation of head and neck anatomy

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Combined tract segmentation and orientation mapping for bundle-specific tractography

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IEEE ACCESS (2019)

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Age-related macular degeneration affects the optic radiation white matter projecting to locations of retinal damage

Shoyo Yoshimine et al.

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Clinical features of demyelinating optic neuritis with seropositive myelin oligodendrocyte glycoprotein antibody in Chinese patients

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Interleaved 3D-CNNs for joint segmentation of small-volume structures in head and neck CT images

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Meyer's loop tractography for image-guided surgery depends on imaging protocol and hardware

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Alterations of the optic pathway between unilateral and bilateral optic nerve damage in multiple sclerosis as revealed by the combined use of advanced diffusion kurtosis imaging and visual evoked potentials

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Automated retinofugal visual pathway reconstruction with multi-shell HARDI and FOD-based analysis

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Optic Radiations Microstructural Changes in Glaucoma and Association With Severity: A Study Using 3Tesla-Magnetic Resonance Diffusion Tensor Imaging

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The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)

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IEEE TRANSACTIONS ON MEDICAL IMAGING (2015)

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Tractography of the optic radiation: a repeatability and reproducibility study

Michael Dayan et al.

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Optic radiation structure and anatomy in the normally developing brain determined using diffusion MRI and tractography

Michael Dayan et al.

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Decoding Diffusivity in Multiple Sclerosis: Analysis of Optic Radiation Lesional and Non-Lesional White Matter

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Robust optic nerve segmentation on clinically acquired computed tomography

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Gibbs tracking: A novel approach for the reconstruction of neuronal pathways

B. W. Kreher et al.

MAGNETIC RESONANCE IN MEDICINE (2008)

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A multiple streamline approach to high angular resolution diffusion tractography

Yi-Ping Chao et al.

MEDICAL ENGINEERING & PHYSICS (2008)

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Geometrical model-based segmentation of the organs of sight on CT images

Gyoergy Bekes et al.

MEDICAL PHYSICS (2008)

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Evaluation of an atlas-based automatic segmentation software for the delineation of brain organs at risk in a radiation therapy clinical context

Aurelie Isambert et al.

RADIOTHERAPY AND ONCOLOGY (2008)

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Article Radiology, Nuclear Medicine & Medical Imaging

Role of magnetic resonance tractography in the preoperative planning and intraoperative assessment of patients with intra-axial brain turnours

A. Romano et al.

RADIOLOGIA MEDICA (2007)

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Article Neurosciences

Characterizing brain anatomical connections using diffusion weighted MRI and graph theory

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NEUROIMAGE (2007)

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Article Neurosciences

Probabilistic diffusion tractography with multiple fibre orientations: What can we gain?

T. E. J. Behrens et al.

NEUROIMAGE (2007)

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Loss of vision:: imaging the visual pathways

HR Jäger

EUROPEAN RADIOLOGY (2005)

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Direct estimation of the fiber orientation density function from diffusion-weighted MRI data using spherical deconvolution

JD Tournier et al.

NEUROIMAGE (2004)

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Article Radiology, Nuclear Medicine & Medical Imaging

Anatomy of the visual system

W Wichmann et al.

EUROPEAN JOURNAL OF RADIOLOGY (2004)

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Article Radiology, Nuclear Medicine & Medical Imaging

Characterization and propagation of uncertainty in diffusion-weighted MR imaging

TEJ Behrens et al.

MAGNETIC RESONANCE IN MEDICINE (2003)

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Article Neurosciences

An error analysis of white matter tractography methods: synthetic diffusion tensor field simulations

M Lazar et al.

NEUROIMAGE (2003)

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Article Radiology, Nuclear Medicine & Medical Imaging

A framework for a streamline-based probabilistic index of connectivity (PICo) using a structural interpretation of MRI diffusion measurements

GJM Parker et al.

JOURNAL OF MAGNETIC RESONANCE IMAGING (2003)

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Article Neurosciences

White matter tractography using diffusion tensor deflection

M Lazar et al.

HUMAN BRAIN MAPPING (2003)

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Article Radiology, Nuclear Medicine & Medical Imaging

Limitations and requirements of diffusion tensor fiber tracking: An assessment using simulations

JD Tournier et al.

MAGNETIC RESONANCE IN MEDICINE (2002)

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Article Radiology, Nuclear Medicine & Medical Imaging

Analysis of partial volume effects in diffusion-tensor MRI

AL Alexander et al.

MAGNETIC RESONANCE IN MEDICINE (2001)

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