Book Review: Neuroimaging: Clinical MR Neuroimaging: Diffusion, Perfusion and Spectroscopy
Bibliographic record
Abstract
Neuroimaging Clinical MR Neuroimaging: Diffusion, Perfusion and Spectroscopy Jonathan H Gillard, Adam D Waldman and Peter B Barker, editors. Cambridge (UK): Cambridge University Press; 2005. 827 p. US$330.00. Reviewer rating: Excellent The last decade has seen a rapidly expanding range of techniques for magnetic resonance imaging (MRI) of the human brain, providing new insights into brain structure, connectivity, and metabolism. These techniques include diffusion, perfusion, and magnetic resonance spectroscopy (MRS). Previously available only in research institutes, they are now becoming accessible on most clinical MR systems. Given their usual research orientation, it is difficult to find guidelines that address both technical details and clinical implications of these methods in an organized and systematized fashion that is accessible to clinicians. The editors of this book, Jonathan H Gillard from the University of Cambridge, Adam D Waldman from Charing Cross Hospital, and Peter B Barker from Johns Hopkins University School of Medicine have achieved this goal. This volume provides an excellent review of the latest MRI methods, from basic physical and technical explanations through to detailed and specific clinical applications. The book is suitable both as an educational manual for beginners and as an up-to-date neuroimaging reference for experienced clinical scientists. The book is divided into 8 major sections (Physiological MR Techniques, Cerebrovascular Disease, Adult Neoplasia, Infection, Inflammation and Demyelination, Seizure Disorders, Psychiatric and Neurodegenerative Diseases, Trauma, and Pediatrics) and into 46 short chapters. All sections are clearly written in an accessible style. Each chapter starts with key points that focus attention on the main concepts. Moreover, the editors have asked many pioneers in their fields (for example, Peter B Barker, Derek K Jones, and Susumi Mori) to write the major sections, making this book even more authoritative. The first section provides an overview of the latest MRI methods with a step-by-step approach that explains the fundamentals of each method in reasonable detail. This section is useful for beginners who are not familiar with, for example, proton spectra of the human brain, anisotropy of water diffusion, or brain hemodynamic indices. The second, and more advanced, section provides methodological approaches to quantification and analysis (for example, in MRS), in diffusion tensor imaging (DTI)-based tractography, or in detection of regional blood flow. …
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.109 | 0.128 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".