The diagnosis of certain spine pathologies, such as scoliosis, spondylolisthesis and vertebral fractures, is part of the daily clinical routine. Very frequently, magnetic resonance image data are used to diagnose these kinds of pathologies in order to avoid exposing patients to harmful radiation, like X-ray. We present a method which detects and segments all acquired vertebral bodies, with minimal user intervention. This allows an automatic diagnosis to detect scoliosis, spondylolisthesis and crushed vertebrae. Our approach consists of three major steps. First, vertebral centres are detected using a Viola-Jones like method, and then the vertebrae are segmented in a parallel manner, and finally, geometric diagnostic features are deduced in order to diagnose the three diseases. Our method was evaluated on 26 lumbar datasets containing 234 reference vertebrae. Vertebra detection has 7.1% false negatives and 1.3% false positives. The average Dice coefficient to manual reference is 79.3% and mean distance error is 1.76 mm. No severe case of the three illnesses was missed, and false alarms occurred rarely-0% for scoliosis, 3.9% for spondylolisthesis and 2.6% for vertebral fractures. The main advantages of our method are high speed, robust handling of a large variety of routine clinical images, and simple and minimal user interaction.

Normal pressure hydrocephalus (NPH) is a clinical syndrome characterized by gait disturbances, urinary incontinence and dementia. Clinical presentation overlaps with Alzheimer disease (AD). Early recognition thus early intervention (shunting) is important for successful treatment, but lack of a diagnostic test with sufficient sensitivity and specificity complicates the diagnosis. We performed literature search and composed a structured review of imaging biomarkers of NPH. Morphometric studies are not sufficient to diagnose NPH. Hydrocephalus is a common finding in elderly people due to the symmetric brain atrophy and is even more pronounced in patients with AD. The key MRI biomarker seems to be diffusion tensor imaging (DTI). According to recent studies, the DTI analysis of the splenium corporis callosi, posterior limb of internal capsule, hippocampus and fornix combined with measurement of Evans index is a promising MRI biomarker of NPH and could be used for NPH diagnostics and in the differential diagnosis from AD and other dementias.

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