The Fraternity of Metaphors: Jean-Luc Godard's Film Socialisme

Since the 'completion' of Histoire(s) du cinema (1988-1998), Jean-Luc Godard's work has become increasingly mosaic-like in its forms and configurations, and markedly elegiac in its ruminations on history, cinema, art, and thought. While his associative aesthetic and citational method –including his choice of ‘actors’, and the fragmentariness of his ‘soundtracks’ – can combine to create a distinctive cinematic event, the films themselves refuse to cohere around a unifying concern, or yield to a thematic schema. Not surprisingly, Film Socialisme does not offer us the illusion of narrative or structural integrity anymore than it contributes to the quotidian rhetoric of political and moral argument. It is, however, a political film in the sense that it alters something more fundamental than opinions and points of view. It transforms a way of seeing and understanding reality and history, fiction and documentary, images, and images of images. If anything, it belongs to that dissident or ‘dissensual’ category of artwork capable of ‘emancipating the spectator’ by disturbing what Jacques Rancière terms ‘the distribution of the sensible’ in that it generates gaps, openings, and spaces, poses questions, invites associations without positing a fixed position, imposing an interpretation, or allowing itself to invest in the illusion of expressive objectivity and the stability of meaning. The myriad citations and fragments that comprise the film are never intended to culminate into anything cohesive, never mind conclusive. In one sense, they have no source and no context beyond their moment in the film itself, and what we make of that moment. This article studies the degree to which Godard allows these images and sounds to combine and collide, associate and dissolve in this film, arguing that Film Socialisme is both an important intervention in the history of contemporary cinema, and necessary point of reference in any serious discussion of the relations between that cinema and political reality.

Travelling Images, Images of Travel in Nicolas Bouvier's L'Usage du monde

Sketches and photographs are a familiar tool of the traveller-writer, who commonly draws on them when transforming experience into a textual narrative. The verbal thus displaces the visual — the latter retained, if at all, as mere illustration — in ways that echo James Heffernan's definition of ekphrasis as the ‘verbal description of visual representation’. Yet Nicolas Bouvier's 1963 travel narrative L'Usage du monde challenges conventional conceptions of ekphrasis. Juxtaposing the stark ink drawings of Thierry Vernet — Bouvier's travelling companion — with Bouvier's textual narrative, L'Usage du monde shifts representation away from a hierarchical relationship between verbal and visual; it offers instead an account of other cultures that is grounded in polyphony and exchange. This article applies Bouvier's own image of travel as a mosaic to the dual narrative form (or ‘iconotext’, to use Michael Nerlich's term) in order to consider a range of fluid relationships between Bouvier's text and Vernet's drawings. In examining these relationships of amplification, reduction, and absence, the article argues that the plurality of the narrative prompts a rethinking of conventional, binary paradigms of intercultural contact. Ultimately, the iconotextual nature of L'Usage du monde can be interpreted as a metaphor for the processes of cultural translation and transculturation that are central to Bouvier's travelling ethos.

Does pre-operative estimation of oesophageal tumour metabolic length using F-18-fluorodeoxyglucose PET/CT images compare with surgical pathology length?

PURPOSE:
The aim of the study was to compare the pre-operative metabolic tumour length on FDG PET/CT with the resected pathological specimen in patients with oesophageal cancer.

METHODS:
All patients diagnosed with oesophageal carcinoma who had undergone staging PET/CT imaging between the period of June 2002 and May 2008 who were then suitable for curative surgery, either with or without neo-adjuvant chemotherapy, were included in this study. Metabolic tumour length was assessed using both visual analysis and a maximum standardised uptake value (SUV(max)) cutoff of 2.5.

RESULTS:
Thirty-nine patients proceeded directly to curative surgical resection, whereas 48 patients received neo-adjuvant chemotherapy, followed by curative surgery. The 95% limits of agreement in the surgical arm were more accurate when the metabolic tumour length was visually assessed with a mean difference of -0.05 cm (SD 2.16 cm) compared to a mean difference of +2.42 cm (SD 3.46 cm) when assessed with an SUV(max) cutoff of 2.5. In the neo-adjuvant group, the 95% limits of agreement were once again more accurate when assessed visually with a mean difference of -0.6 cm (SD 1.84 cm) compared to a mean difference of +1.58 cm (SD 3.1 cm) when assessed with an SUV(max) cutoff of 2.5.

CONCLUSION:
This study confirms the high accuracy of PET/CT in measuring gross target volume (GTV) length. A visual method for GTV length measurement was demonstrated to be superior and more accurate than when using an SUV(max) cutoff of 2.5. This has the potential of reducing the planning target volume with dose escalation to the tumour with a corresponding reduction in normal tissue complication probability.

Ultra-fast processing of gigapixel Tissue MicroArray images using high performance computing.

BACKGROUND:
tissue MicroArrays (TMAs) are a valuable platform for tissue based translational research and the discovery of tissue biomarkers. The digitised TMA slides or TMA Virtual Slides, are ultra-large digital images, and can contain several hundred samples. The processing of such slides is time-consuming, bottlenecking a potentially high throughput platform.
METHODS:
a High Performance Computing (HPC) platform for the rapid analysis of TMA virtual slides is presented in this study. Using an HP high performance cluster and a centralised dynamic load balancing approach, the simultaneous analysis of multiple tissue-cores were established. This was evaluated on Non-Small Cell Lung Cancer TMAs for complex analysis of tissue pattern and immunohistochemical positivity.
RESULTS:
the automated processing of a single TMA virtual slide containing 230 patient samples can be significantly speeded up by a factor of circa 22, bringing the analysis time to one minute. Over 90 TMAs could also be analysed simultaneously, speeding up multiplex biomarker experiments enormously.
CONCLUSIONS:
the methodologies developed in this paper provide for the first time a genuine high throughput analysis platform for TMA biomarker discovery that will significantly enhance the reliability and speed for biomarker research. This will have widespread implications in translational tissue based research.

Assessing the image quality of pelvic MR images acquired with a flat couch for radiotherapy treatment planning

Objectives: To improve the integration of MRI with radiotherapy treatment planning, our department fabricated a flat couch top for our MR scanner. Setting up using this couch top meant that the patients were physically higher up in the scanner and, posteriorly, a gap was introduced between the patient and radiofrequency coil.

Nonrigid Structure-From-Motion From 2-D Images Using Markov Chain Monte Carlo

In this paper we present a new method for simultaneously determining three dimensional (3-D) shape and motion of a non-rigid object from uncalibrated two dimensional (2- D) images without assuming the distribution characteristics. A non-rigid motion can be treated as a combination of a rigid rotation and a non-rigid deformation. To seek accurate recovery of deformable structures, we estimate the probability distribution function of the corresponding features through random sampling, incorporating an established probabilistic model. The fitting between the observation and the projection of the estimated 3-D structure will be evaluated using a Markov chain Monte Carlo based expectation maximisation algorithm. Applications of the proposed method to both synthetic and real image sequences are demonstrated with promising results.

Robust automated tumour segmentation on histological and immunohistochemical tissue images

Tissue microarray (TMA) is a high throughput analysis tool to identify new diagnostic and prognostic markers in human cancers. However, standard automated method in tumour detection on both routine histochemical and immunohistochemistry (IHC) images is under developed. This paper presents a robust automated tumour cell segmentation model which can be applied to both routine histochemical tissue slides and IHC slides and deal with finer pixel-based segmentation in comparison with blob or area based segmentation by existing approaches. The presented technique greatly improves the process of TMA construction and plays an important role in automated IHC quantification in biomarker analysis where excluding stroma areas is critical. With the finest pixel-based evaluation (instead of area-based or object-based), the experimental results show that the proposed method is able to achieve 80% accuracy and 78% accuracy in two different types of pathological virtual slides, i.e., routine histochemical H&E and IHC images, respectively. The presented technique greatly reduces labor-intensive workloads for pathologists and highly speeds up the process of TMA construction and provides a possibility for fully automated IHC quantification.