Analysis of Signal Decomposition and Stain Separation methods for biomedical applications

Nowadays, the biomedical signal processing and classification and medical image interpretation play an essential role in the detection and diagnosis of several human diseases. The problem of high variability and heterogeneity of information, which is extracted from digital data, can be addressed with signal decomposition and stain separation techniques which can be useful approaches to highlight hidden patterns or rhythms in biological signals and specific cellular structures in histological color images, respectively. This thesis work can be divided into two macro-sections. In the first part (Part I), a novel cascaded RNN model based on long short-term memory (LSTM) blocks is presented with the aim to classify sleep stages automatically. A general workflow based on single-channel EEG signals is developed to enhance the low performance in staging N1 sleep without reducing the performances in the other sleep stages (i.e. Wake, N2, N3 and REM). In the same context, several signal decomposition techniques and time-frequency representations are deployed for the analysis of EEG signals. All extracted features are analyzed by using a novel correlation-based timestep feature selection and finally the selected features are fed to a bidirectional RNN model. In the second part (Part II), a fully automated method named SCAN (Stain Color Adaptive Normalization) is proposed for the separation and normalization of staining in digital pathology. This normalization system allows to standardize digitally, automatically and in a few seconds, the color intensity of a tissue slide with respect to that of a target image, in order to improve the pathologist’s diagnosis and increase the accuracy of computer-assisted diagnosis (CAD) systems. Multiscale evaluation and multi-tissue comparison are performed for assessing the robustness of the proposed method. In addition, a stain normalization based on a novel mathematical technique, named ICD (Inverse Color Deconvolution) is developed for immunohistochemical (IHC) staining in histopathological images. In conclusion, the proposed techniques achieve satisfactory results compared to state-of-the-art methods in the same research field. The workflow proposed in this thesis work and the developed algorithms can be employed for the analysis and interpretation of other biomedical signals and for digital medical image analysis

Electrolytic Reduction of Indigo in Pyridine Application to the Determination of Dissolved Oxygen

The electrochemical reduction of indigo in pyridine as solvent has been investigated in connection with the determination of oxygen dissolved in pyridine, using polarography, cyclic voltammetry, controlled electrode potential electrolysis and coulometry. In the absence of protons, the total current of the first and second reduction waves for an unsaturated solution of indigo (LiClO 4 as background electrolyte) apparently represents a one‐electron transfer. In the presence of an excess of available protons (added as pyridinium nitrate), indigo is reduced in a reversible two‐electron process to indigo white (leucoindigo). The rapid conversion of indigo white to indigo by oxygen in pyridine solution can be used to determine coulometrically the concentration of oxygen in pyridine via measurement of the indigo produced on adding the pyridine‐oxygen sample to a solution of in situ electrolytically generated indigo white. The latter approach indicated a general method for the determination of dissolved oxygen in nonaqueous solvents.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/101790/1/197000109_ftp.pd

Automatic Optic Nerve Measurement: A New Tool to Standardize Optic Nerve Assessment in Ultrasound B-Mode Images

Transorbital sonography provides reliable information about the estimation of intra-cranial pressure by measuring the optic nerve sheath diameter (ONSD), whereas the optic nerve (ON) diameter (OND) may reveal ON atrophy in patients with multiple sclerosis. Here, an AUTomatic Optic Nerve MeAsurement (AUTONoMA) system for OND and ONSD assessment in ultrasound B-mode images based on deformable models is presented. The automated measurements were compared with manual ones obtained by two operators, with no significant differences. AUTONoMA correctly segmented the ON and its sheath in 71 out of 75 images. The mean error compared with the expert operator was 0.06 ± 0.52 mm and 0.06 ± 0.35 mm for the ONSD and OND, respectively. The agreement between operators and AUTONoMA was good and a positive correlation was found between the readers and the algorithm with errors comparable with the inter-operator variability. The AUTONoMA system may allow for standardization of OND and ONSD measurements, reducing manual evaluation variability

Multimodal T2w and DWI Prostate Gland Automated Registration

Multiparametric magnetic resonance imaging (mpMRI) is emerging as a promising tool in the clinical pathway of prostate cancer (PCa). The registration between a structural and a functional imaging modality, such as T2-weighted (T2w) and diffusion-weighted imaging (DWI) is fundamental in the development of a mpMRI-based computer aided diagnosis (CAD) system for PCa. Here, we propose an automated method to register the prostate gland in T2w and DWI image sequences by a landmark-based affine registration and a non-parametric diffeomorphic registration. An expert operator manually segmented the prostate gland in both modalities on a dataset of 20 patients. Target registration error and Jaccard index, which measures the overlap between masks, were evaluated pre-and post-registration resulting in an improvement of 44% and 21%, respectively. In the future, the proposed method could be useful in the framework of a CAD system for PCa detection and characterization in mpMRI

OD26 - Inverse consistency error as a validation metric for deformable image registration: preliminary implementation research

The aim of this work is to develop a novel automatic voxel-based quantitative measurement approach to evaluate the registration accuracy of a Deformable Image Registration (DIR) algorithm in clinical practice. As the Inverse Consistency Error (ICE) can be computed directly from the deformation vector field (DVF) generated by the Treatment Planning System (TPS), it appears to be a valid surrogate of standard quality assurance metrics to assess the spatial error in the registration process

Automatic Extraction of Dermatological Parameters from Nevi Using an Inexpensive Smartphone Microscope: A Proof of Concept

The evolution of smartphone technology has made their use more common in dermatological applications. Here we studied the feasibility of using an inexpensive smartphone microscope for the extraction of dermatological parameters and compared the results obtained with a portable dermoscope, commonly used in clinical practice. Forty-two skin lesions were imaged with both devices and visually analyzed by an expert dermatologist. The presence of a reticular pattern was observed in 22 dermoscopic images, but only in 10 smartphone images. The proposed paradigm segments the image and extracts texture features which are used to train and validate a neural network to classify the presence of a reticular pattern. Using 5-fold cross-validation, an accuracy of 100% and 95% was obtained with the dermoscopic and smartphone images, respectively. This approach can be useful for general practitioners and as a triage tool for skin lesion analysis

L'Enterprise Risk Management applicato ai rischi ambientali: il caso G.I.D.A. S.p.A.

Il presente elaborato di tesi ha l'obiettivo di analizzare le tematiche e la filosofia di fondo della gestione del rischio aziendale in un contesto economico e finanziario sempre più globale, imprevedibile e turbolento evidenziando la necessità di disporre di un valido modello di supporto metodologico per identificare, valutare e gestire i rischi in modo efficace. Da qui deriva l’attuale riconoscimento al tema del Risk Management come elemento irrinunciabile dell'attività imprenditoriale come fattore critico di successo per il perseguimento di un equilibrio economico a valere nel tempo. Il lavoro proseguirà argomentando l'Enterprise Risk Management - Integrated Framework in quanto modello di riferimento nel sistema di controllo interno e gestione dei rischi, specificando i suoi componenti, il ruolo e le responsabilità degli attori coinvolti nonché i limiti e le problematiche connesse allo stesso processo di implementazione. A completamento di quanto suddetto, si richiamerà l'International Standard ISO 31000 "Risk management - Principles and guidelines" analizzando la relazione tra i principi, la struttura ed il processo di gestione del rischio così come dettato dalla norma. L'ultima parte dell'elaborato sarà, infine, dedicata alla esplicitazione del caso pratico implementato presso l'azienda G.I.D.A. S.p.A., attraverso un progetto di tirocinio curriculare. La procedura di valutazione dei rischi, realizzata in seno alla Società e articolata nelle sue fasi di identificazione, analisi e ponderazione dei rischi, riguarderà specificatamente i processi di trattamento liquami e smaltimento fanghi, al fine di segnalare gli eventi rischiosi ritenuti significativi in termini di impatto ambientale: l'esito della procedura sarà illustrato sinteticamente attraverso l'impiego di una matrice di significatività. Sulla base di tali risultanze si descriveranno i principali interventi che la Società intende porre in essere, a testimonianza dell'incidenza che la variabile rischio assume nel processo decisionale aziendale