Visual parameter optimisation for biomedical image processing

Background: Biomedical image processing methods require users to optimise input parameters to ensure high quality output. This presents two challenges. First, it is difficult to optimise multiple input parameters for multiple input images. Second, it is difficult to achieve an understanding of underlying algorithms, in particular, relationships between input and output. Results: We present a visualisation method that transforms users’ ability to understand algorithm behaviour by integrating input and output, and by supporting exploration of their relationships. We discuss its application to a colour deconvolution technique for stained histology images and show how it enabled a domain expert to identify suitable parameter values for the deconvolution of two types of images, and metrics to quantify deconvolution performance. It also enabled a breakthrough in understanding by invalidating an underlying assumption about the algorithm. Conclusions: The visualisation method presented here provides analysis capability for multiple inputs and outputs in biomedical image processing that is not supported by previous analysis software. The analysis supported by our method is not feasible with conventional trial-and-error approaches

Biomedical Image Processing and Classification

Biomedical image processing is an interdisciplinary field [...

Biomedical Image Processing and Classification

Biomedical image processing is an interdisciplinary field involving a variety of disciplines, e.g., electronics, computer science, physics, mathematics, physiology, and medicine. Several imaging techniques have been developed, providing many approaches to the study of the human body. Biomedical image processing is finding an increasing number of important applications in, for example, the study of the internal structure or function of an organ and the diagnosis or treatment of a disease. If associated with classification methods, it can support the development of computer-aided diagnosis (CAD) systems, which could help medical doctors in refining their clinical picture

Neuromorphic electronics for real-time biomedical image processing

Published versio

Review of Biomedical Image Processing

This article is a review of the book: 'Biomedical Image Processing', by Thomas M. Deserno, which is published by Springer-Verlag. Salient information that will be useful to decide whether the book is relevant to topics of interest to the reader, and whether it might be suitable as a course textbook, are presented in the review. This includes information about the book details, a summary, the suitability of the text in course and research work, the framework of the book, its specific content, and conclusions

Multimodal techniques for biomedical image processing

Il lavoro di dottorato ha coinvolto tre principali aree di ricerca biomedica. Nella prima area, abbiamo mirato a valutare se le misure del tempo di rilassamento T1 in Risonanza Magnetica possono contribuire ad individuare dei predittori strutturali di lievi disturbi cognitivi in pazienti con forma Recidivante-Remittente di Sclerosi Multipla(RRMS). Ventinove controlli sani (HC) e quarantanove RRMS pazienti sono stati sottoposti a Risonanza magnetica a 3T per acquisire in maniera ottimale per la zona corticale e per la sostanza bianca (WML), i tempi di rilassamento T1 (rt), la conta delle lesioni e il volume. Nella WML e in quelle di tipo CL I (sostanza bianca - grigia mista), i T1 rt z-score sono risultati, significativamente, pi\uf9 lunghi rispetto ai tessuti dei controlli HC (p<0.001 e p<0.01, rispettivamente), indice di un\u2019impoverimento del tessuto cerebrale. L'analisi di regressione multivariata ha rivelato che: i T1 rt z-score nelle lesioni corticali sono predittori indipendenti del recupero della memoria a lungo termine (p=0.01), i T1 z -score nella lesioni corticali della materia bianca sono predittori indipendenti del deficit relativi all\u2019attenzione prolungata e all\u2019elaborazione delle informazioni (p=0,02) ; Nella seconda, descriviamo un suscettometro biomagnetico a temperatura ambiente in grado di quantificare il sovraccarico di ferro nel fegato. Tramite un campo magnetico modulato elettronicamente, il sistema riesce a misurare segnali magnetici 108 volte pi\uf9 piccoli del campo applicato. Il rumore meccanico del suscettometro a temperatura ambiente viene minimizzato e il drift termico viene monitorato da un sistema automatico di bilanciamento. Abbiamo testato e calibrato lo strumento utilizzando un fantoccio riempito con una soluzione di esacloruro esaidrato II di ferro, ottenendo come correlazione R = 0,98 tra la massima risposta del suscettometro e la concentrazione di ferro. Queste misure indicano che per garantire una buon funzionamento dello strumento con una variabilit\ue0 del segnale di uscita pari al 4-5%, eguale a circa 500ugr/gr di ferro, il tempo di acquisizione deve essere minore o uguale a 8 secondi. Nela terza area, un'analisi agli elementi finiti del modello 3D anatomicamente dettagliato del piede umano \ue8 il risultato finale della segmentazione 3D, secondo tecniche di ricostruzione applicate ad immagini standard DICOM di scansione a Tomografia Computerizzata, in congiunzione con la modellazione 3D assistita e dell\u2019analisi agli elementi finiti (FEA). In questo modello la reale morfologia del cuscinetto adiposo plantare \ue8 stato considerata: \ue8 stato dimostrato giocare un ruolo molto importante durante il contatto con il terreno. Per ottenere i dati sperimentali da confrontare con le predizioni del modello 3D del piede, un esame posturografico statico su una pedana baropodometrica \ue8 stato effettuato. La pressione sperimentale del contatto plantare \ue8 risultata, qualitativamente, comparabile con i risultati predetti dall\u2019analisi agli elementi finiti, principalmente, confrontando i valori sperimentali con i valori massimi delle pressioni in corrispondenza delle zona centrali del tallone e sotto le teste metatarsali.The PhD work involved three main biomedical research areas. In the first, we aimed at assessing whether T1 relaxometry measurements may help identifying structural predictors of mild cognitive impairments in patients with relapsing-remitting multiple sclerosis. Twenty-nine healthy controls and forty-nine RRMS patients underwent at high resolution 3T magnetic resonance imaging to obtain optimal cortical and white matter lesion count/volume as well as T1 relaxation times (rt). In WML and CL type I (mixed white-gray matter), T1 rt z-scores were significantly longer than in HC tissue (p<0.001 and p<0.01 respectively), indicating loss of structure. Multivariate analysis revealed T1 rt z-scores in CL type I were independent predictors of long term retrieval (p=0.01), T1 z-score relaxation time in white matter cortical lesions were independent predictors of sustained attention and information processing (p=0.02); In the second, we describe a biomagnetic susceptometer at room-temperature to quantify liver iron overload. By electronically modulated magnetic field, the magnetic system measure magnetic signal 108 times weaker than field applied. The mechanical noise of room-temperature susceptometer is cancelled and thermal drift is monitored by an automatic balance control system. We have tested and calibrated the system using cylindrical phantom filled with hexahydrated iron II choloride solution, obtaining the correlation (R=0.98) of the maximum variation in the responses of the susceptometer. These measures indicate that the acquisition time must be less than 8 seconds to guarantee an output signal variability to about 4-5%, equal to 500ugr/grwet of iron. In the third, a 3D anatomically detailed finite element analysis human foot model is final results of density segmentation 3D reconstruction techiniques applied in Computed Tomography(CT) scan DICOM standard images in conjunctions with 3D finite element analysis(FEA) modeling. In this model the real morphology of plantar fat pad has been considered: it was shown to play a very important role during the contact with the ground. To obtain the experimental data to compare the predictions of 3D foot model, a posturography static examination test on a baropodometric platform has been carried. The experimental plantar contact pressure is, qualitatively, comparable with FEA predicted results, nominally, the peak pressure value zones at the centre heel region and beneath the metatarsal heads