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1. Sagittal Craniosynostosis: Comparing Surgical Techniques Using 3D Photogrammetry

2. Computer-Aided Diagnosis and Prediction in Brain Disorders

3. Association between prenatal alcohol exposure and children's facial shape:: a prospective population-based cohort study

4. Towards quantitative digital subtraction perfusion angiography: An animal study

5. Evaluation of AR visualization approaches for catheter insertion into the ventricle cavity

6. Combined molecular subtyping, grading, and segmentation of glioma using multi-task deep learning

7. Subclinical liver traits are associated with structural and hemodynamic brain imaging markers

8. Deep reinforcement learning for cerebral anterior vessel tree extraction from 3D CTA images

9. Multi-view Contour-constrained Transformer Network for Thin-cap Fibroatheroma Identification

10. Augmented reality navigation for minimally invasive craniosynostosis surgery: a phantom study

11. Classification of clinically significant prostate cancer on multi-parametric MRI: A validation study comparing deep learning and radiomics

12. Spatio-temporal deep learning for automatic detection of intracranial vessel perforation in digital subtraction angiography during endovascular thrombectomy

13. Multimodal markers for technology-independent integration of augmented reality devices and surgical navigation systems

14. Evaluation of Marker Tracking Using Mono and Stereo Vision in Microsoft HoloLens for Surgical Navigation

15. Evaluation of Marker Tracking Using Mono and Stereo Vision in Microsoft HoloLens for Surgical Navigation

16. Augmented reality navigation for minimally invasive craniosynostosis surgery: a phantom study

17. Multimodal markers for technology-independent integration of augmented reality devices and surgical navigation systems

18. Spatio-temporal deep learning for automatic detection of intracranial vessel perforation in digital subtraction angiography during endovascular thrombectomy

19. Classification of clinically significant prostate cancer on multi-parametric MRI: A validation study comparing deep learning and radiomics

20. Differential Diagnosis and Molecular Stratification of Gastrointestinal Stromal Tumors on CT Images Using a Radiomics Approach

21. Progression along data-driven disease timelines is predictive of Alzheimer's disease in a population-based cohort

22. Differences Between MR Brain Region Segmentation Methods: Impact on Single-Subject Analysis

23. Resistance to developing brain pathology due to vascular risk factors: the role of educational attainment

24. Cross-cohort generalizability of deep and conventional machine learning for MRI-based diagnosis and prediction of Alzheimer's disease

25. A multi-center, multi-vendor study to evaluate the generalizability of a radiomics model for classifying prostate cancer: High grade vs. low grade

26. Recurrent inference machines as inverse problem solvers for MR relaxometry

27. Distinguishing pure histopathological growth patterns of colorectal liver metastases on CT using deep learning and radiomics: a pilot study

28. Associations of thrombus perviousness derived from entire thrombus segmentation with functional outcome in patients with acute ischemic stroke

29. GenNet framework: interpretable deep learning for predicting phenotypes from genetic data

30. The BRAF P.V600E Mutation Status of Melanoma Lung Metastases Cannot Be Discriminated on Computed Tomography by LIDC Criteria nor Radiomics Using Machine Learning

31. Longitudinal diffusion MRI analysis using Segis-Net: A single-step deep-learning framework for simultaneous segmentation and registration

32. Genetic Determinants of Cortical Structure (Thickness, Surface Area and Volumes) among Disease Free Adults in the CHARGE Consortium

33. Differences Between MR Brain Region Segmentation Methods: Impact on Single-Subject Analysis

34. GenNet framework: interpretable deep learning for predicting phenotypes from genetic data

35. Associations of thrombus perviousness derived from entire thrombus segmentation with functional outcome in patients with acute ischemic stroke

36. Distinguishing pure histopathological growth patterns of colorectal liver metastases on CT using deep learning and radiomics: a pilot study

37. Resistance to developing brain pathology due to vascular risk factors: the role of educational attainment

38. Recurrent inference machines as inverse problem solvers for MR relaxometry

39. A multi-center, multi-vendor study to evaluate the generalizability of a radiomics model for classifying prostate cancer: High grade vs. low grade

40. Cross-cohort generalizability of deep and conventional machine learning for MRI-based diagnosis and prediction of Alzheimer's disease

41. Longitudinal diffusion MRI analysis using Segis-Net: A single-step deep-learning framework for simultaneous segmentation and registration

42. The BRAF P.V600E Mutation Status of Melanoma Lung Metastases Cannot Be Discriminated on Computed Tomography by LIDC Criteria nor Radiomics Using Machine Learning

43. Differential diagnosis and mutation stratification of desmoid-type fibromatosis on MRI using radiomics

44. Genetic correlations and genome-wide associations of cortical structure in general population samples of 22,824 adults

45. Neuro4Neuro: A neural network approach for neural tract segmentation using large-scale population-based diffusion imaging

46. Predicting Global Cognitive Decline in the General Population Using the Disease State Index

47. Analyzing the effect of APOE on Alzheimer's disease progression using an event-based model for stratified populations

48. Cerebral small vessel disease genomics and its implications across the lifespan

49. Cerebral blood flow and cognitive functioning in patients with disorders along the heart–brain axis: Cerebral blood flow and the heart–brain axis

50. Automated classification of significant prostate cancer on MRI: A systematic review on the performance of machine learning applications

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