Mass detection on mammograms: influence of signal shape uncertainty on human and model observers.

We studied the influence of signal variability on human and model observers for detection tasks with realistic simulated masses superimposed on real patient mammographic backgrounds and synthesized mammographic backgrounds (clustered lumpy backgrounds, CLB). Results under the signal-known-exactly (SKE) paradigm were compared with signal-known-statistically (SKS) tasks for which the observers did not have prior knowledge of the shape or size of the signal. Human observers' performance did not vary significantly when benign masses were superimposed on real images or on CLB. Uncertainty and variability in signal shape did not degrade human performance significantly compared with the SKE task, while variability in signal size did. Implementation of appropriate internal noise components allowed the fit of model observers to human performance.

Optical spectroscopy of the bladder washout fluid to optimize fluorescence cystoscopy with Hexvix®.

Fluorescence cystoscopy enhances detection of early bladder cancer. Water used to inflate the bladder during the procedure rapidly contains urine, which may contain fluorochromes. This frequently degradesfluorescence images. Samples of bladder washout fluid (BWF) or urine were collected (15 subjects). We studiedtheir fluorescence properties and assessed changes induced by pH (4 to 9) and temperature (15°C to 41°C).A typical fluorescence spectrum of BWF features a main peak (excitation/emission: 320∕420 nm, FWHM =50∕100 nm) and a weaker (5% to 20% of main peak intensity), secondary peak (excitation/emission: 455∕525 nm, FWHM = 80∕50 nm). Interpatient fluctuations of fluorescence intensity are observed. Fluorescence intensity decreases when temperature increases (max 30%) or pH values vary (max 25%). Neither approach is compatible with clinical settings. Fluorescence lifetime measurements suggest that 4-pyridoxic acid/riboflavin is the most likely molecule responsible for urine's main/secondary fluorescence peak. Our measurements give an insight into the spectroscopy of the detrimental background fluorescence. This should be included in the optical design of fluorescence cystoscopes. We estimate that restricting the excitation range from 370-430 nm to 395-415 nm would reduce the BWF background by a factor 2.

Multi-modal Change Detection, Application to the Detection of Flooded Areas: Outcome of the 2009-2010 data fusion contest

The 2009-2010 Data Fusion Contest organized by the Data Fusion Technical Committee of the IEEE Geoscience and Remote Sensing Society was focused on the detection of flooded areas using multi-temporal and multi-modal images. Both high spatial resolution optical and synthetic aperture radar data were provided. The goal was not only to identify the best algorithms (in terms of accuracy), but also to investigate the further improvement derived from decision fusion. This paper presents the four awarded algorithms and the conclusions of the contest, investigating both supervised and unsupervised methods and the use of multi-modal data for flood detection. Interestingly, a simple unsupervised change detection method provided similar accuracy as supervised approaches, and a digital elevation model-based predictive method yielded a comparable projected change detection map without using post-event data.

Risk Evaluation for Spoofing against a Sensor Supplied with Liveness Detection

The aim of this paper is to evaluate the risks associated with the use of fake fingerprints on a livescan supplied with a method of liveness detection. The method is based on optical properties of the skin. The sensor uses several polarizations and illuminations to capture the information of the different layers of the human skin. These experiments also allow for the determination under which conditions the system is deceived and if there is an influence respectively of the nature of the fake, the mould used for the production or the individuals involved in the attack. These experiments showed that current multispectral sensors can be deceived by the use of fake fingerprints created with or without the cooperation of the subject. Fakes created from direct casts perform better than those produced by fakes created from indirect casts. The results showed that the success of the attack is influenced by two main factors. The first is the quality of the fakes, and by extension the quality of the original fingerprint. The second is the combination of the general patterns involved in the attacks since an appropriate combination can strongly increase the rates of successful attacks.

Kernel-based methods for change detection in remote sensing images

Nowadays, the joint exploitation of images acquired daily by remote sensing instruments and of images available from archives allows a detailed monitoring of the transitions occurring at the surface of the Earth. These modifications of the land cover generate spectral discrepancies that can be detected via the analysis of remote sensing images. Independently from the origin of the images and of type of surface change, a correct processing of such data implies the adoption of flexible, robust and possibly nonlinear method, to correctly account for the complex statistical relationships characterizing the pixels of the images. This Thesis deals with the development and the application of advanced statistical methods for multi-temporal optical remote sensing image processing tasks. Three different families of machine learning models have been explored and fundamental solutions for change detection problems are provided. In the first part, change detection with user supervision has been considered. In a first application, a nonlinear classifier has been applied with the intent of precisely delineating flooded regions from a pair of images. In a second case study, the spatial context of each pixel has been injected into another nonlinear classifier to obtain a precise mapping of new urban structures. In both cases, the user provides the classifier with examples of what he believes has changed or not. In the second part, a completely automatic and unsupervised method for precise binary detection of changes has been proposed. The technique allows a very accurate mapping without any user intervention, resulting particularly useful when readiness and reaction times of the system are a crucial constraint. In the third, the problem of statistical distributions shifting between acquisitions is studied. Two approaches to transform the couple of bi-temporal images and reduce their differences unrelated to changes in land cover are studied. The methods align the distributions of the images, so that the pixel-wise comparison could be carried out with higher accuracy. Furthermore, the second method can deal with images from different sensors, no matter the dimensionality of the data nor the spectral information content. This opens the doors to possible solutions for a crucial problem in the field: detecting changes when the images have been acquired by two different sensors.

Compact portable biosensor for arsenic detection in aqueous samples with Escherichia coli bioreporter cells.

We present a compact portable biosensor to measure arsenic As(III) concentrations in water using Escherichia coli bioreporter cells. Escherichia coli expresses green fluorescent protein in a linearly dependent manner as a function of the arsenic concentration (between 0 and 100 μg/L). The device accommodates a small polydimethylsiloxane microfluidic chip that holds the agarose-encapsulated bacteria, and a complete optical illumination/collection/detection system for automated quantitative fluorescence measurements. The device is capable of sampling water autonomously, controlling the whole measurement, storing and transmitting data over GSM networks. We demonstrate highly reproducible measurements of arsenic in drinking water at 10 and 50 μg/L within 100 and 80 min, respectively.

Landmark detection for fusion of fundus and MRI toward a patient-specific multimodal eye model.

Ophthalmologists typically acquire different image modalities to diagnose eye pathologies. They comprise, e.g., Fundus photography, optical coherence tomography, computed tomography, and magnetic resonance imaging (MRI). Yet, these images are often complementary and do express the same pathologies in a different way. Some pathologies are only visible in a particular modality. Thus, it is beneficial for the ophthalmologist to have these modalities fused into a single patient-specific model. The goal of this paper is a fusion of Fundus photography with segmented MRI volumes. This adds information to MRI that was not visible before like vessels and the macula. This paper contributions include automatic detection of the optic disc, the fovea, the optic axis, and an automatic segmentation of the vitreous humor of the eye.

Risk evaluation for spoofing against a sensor supplied with liveness detection

The aim of this paper is to evaluate the risks associated with the use of fake fingerprints on a livescan supplied with a method of liveness detection. The method is based on optical properties of the skin. The sensor uses several polarizations and illuminations to capture the information of the different layers of the human skin. These experiments also allow for the determination under which conditions the system is deceived and if there is an influence respectively of the nature of the fake, the mould used for the production or the individuals involved in the attack. These experiments showed that current multispectral sensors can be deceived by the use of fake fingerprints created with or without the cooperation of the subject. Fakes created from direct casts perform better than those produced by fakes created from indirect casts. The results showed that the success of the attack is influenced by two main factors. The first is the quality of the fakes, and by extension the quality of the original fingerprint. The second is the combination of the general patterns involved in the attacks since an appropriate combination can strongly increase the rates of successful attacks.

Landmark detection for fusion of fundus and MRI toward a patient-specific multimodal eye model.

Ophthalmologists typically acquire different image modalities to diagnose eye pathologies. They comprise, e.g., Fundus photography, optical coherence tomography, computed tomography, and magnetic resonance imaging (MRI). Yet, these images are often complementary and do express the same pathologies in a different way. Some pathologies are only visible in a particular modality. Thus, it is beneficial for the ophthalmologist to have these modalities fused into a single patient-specific model. The goal of this paper is a fusion of Fundus photography with segmented MRI volumes. This adds information to MRI that was not visible before like vessels and the macula. This paper contributions include automatic detection of the optic disc, the fovea, the optic axis, and an automatic segmentation of the vitreous humor of the eye.

Cadmium-free quantum dots in aqueous solution: potential for fingermark detection, synthesis and an application to the detection of fingermarks in blood on non-porous surfaces

The use of quantum dots (QDs) in the area of fingermark detection is currently receiving a lot of attention in the forensic literature. Most of the research efforts have been devoted to cadmium telluride (CdTe) quantum dots often applied as powders to the surfaces of interests. Both the use of cadmium and the nano size of these particles raise important issues in terms of health and safety. This paper proposes to replace CdTe QDs by zinc sulphide QDs doped with copper (ZnS:Cu) to address these issues. Zinc sulphide-copper doped QDs were successfully synthesized, characterized in terms of size and optical properties and optimized to be applied for the detection of impressions left in blood, where CdTe QDs proved to be efficient. Effectiveness of detection was assessed in comparison with CdTe QDs and Acid Yellow 7 (AY7, an effective blood reagent), using two series of depletive blood fingermarks from four donors prepared on four non-porous substrates, i.e. glass, transparent polypropylene, black polyethylene and aluminium foil. The marks were cut in half and processed separately with both reagents, leading to two comparison series (ZnS:Cu vs. CdTe, and ZnS:Cu vs. AY7). ZnS:Cu proved to be better than AY7 and at least as efficient as CdTe on most substrates. Consequently, copper-doped ZnS QDs constitute a valid substitute for cadmium-based QDs to detect blood marks on non-porous substrates and offer a safer alternative for routine use.