Glaucoma is a group of eye diseases which can cause vision loss by damaging the optic nerve. Early glaucoma detection is key to preventing vision loss yet there is a lack of noticeable early symptoms. Colour fundus photography allows the optic disc (OD) to be examined to diagnose glaucoma. Typically, this is done by measuring the vertical cup-to-disc ratio (CDR); however, glaucoma is characterised by thinning of the rim asymmetrically in the inferior-superior-temporal-nasal regions in increasing order. Automatic delineation of the OD features has potential to improve glaucoma management by allowing for this asymmetry to be considered in the measurements. Here, we propose a new deep-learning-based method to segment the OD and optic cup (OC). The core of the proposed method is DenseNet with a fully-convolutional network, whose symmetric U-shaped architecture allows pixel-wise classification. The predicted OD and OC boundaries are then used to estimate the CDR on two axes for glaucoma diagnosis. We assess the proposed method's performance using a large retinal colour fundus dataset, outperforming state-of-the-art segmentation methods. Furthermore, we generalise our method to segment four fundus datasets from different devices without further training, outperforming the state-of-the-art on two and achieving comparable results on the remaining two.

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Research has recently demonstrated that larval zebrafish show similar molecular responses to nociception to those of adults. Our study explored whether unprotected larval zebrafish exhibited altered behaviour after exposure to noxious chemicals and screened a range of analgesic drugs to determine their efficacy to reduce these responses. This approach aimed to validate larval zebrafish as a reliable replacement for adults as well as providing a high-throughput means of analysing behavioural responses. Zebrafish at 5 days postfertilization were exposed to known noxious stimuli: acetic acid (0.01%, 0.1% and 0.25%) and citric acid (0.1%, 1% and 5%). The behavioural response of each was recorded and analysed using novel tracking software that measures time spent active in 25 larvae at one time. Subsequently, the efficacy of aspirin, lidocaine, morphine and flunixin as analgesics after exposure to 0.1% acetic acid was tested. Larvae exposed to 0.1% and 0.25% acetic acid spent less time active, whereas those exposed to 0.01% acetic acid and 0.1-5% citric acid showed an increase in swimming activity. Administration of 2.5 mg l −1 aspirin, 5 mg l −1 lidocaine and 48 mg l −1 morphine prevented the behavioural changes induced by acetic acid. These results suggest that larvae respond to a noxious challenge in a similar way to adult zebrafish and other vertebrates and that the effect of nociception on activity can be ameliorated by using analgesics. Therefore, adopting larval zebrafish could represent a direct replacement of a protected adult fish with a non-protected form in pain-and nociception-related research.

Fish are used in a variety of experimental contexts often in high numbers. To maintain their welfare and ensure valid results during invasive procedures it is vital that we can detect subtle changes in behaviour that may allow us to intervene to provide pain-relief. Therefore, an automated method, the Fish Behaviour Index (FBI), was devised and used for testing the impact of laboratory procedures and efficacy of analgesic drugs in the model species, the zebrafish. Cameras with tracking software were used to visually track and quantify female zebrafish behaviour in real time after a number of laboratory procedures including fin clipping, PIT tagging, and nociceptor excitation via injection of acetic acid subcutaneously. The FBI was derived from activity and distance swum measured before and after these procedures compared with control and sham groups. Further, the efficacy of a range of drugs with analgesic properties to identify efficacy of these agents was explored. Lidocaine (5 mg/L), flunixin (8 mg/L) and morphine (48 mg/L) prevented the associated reduction in activity and distance swum after fin clipping. From an ethical perspective, the FBI represents a significant refinement in the use of zebrafish and could be adopted across a wide range of biological disciplines.

The retinal fundus photograph is widely used in the diagnosis and treatment of various eye diseases such as diabetic retinopathy and glaucoma. Medical image analysis and processing has great significance in the field of medicine, especially in non-invasive treatment and clinical study. Normally fundus images are manually graded by specially trained clinicians in a time-consuming and resource-intensive process. A computer-aided fundus image analysis could provide an immediate detection and characterisation of retinal features prior to specialist inspection. This paper describes a novel method to automatically localise one such feature: the optic disk. The proposed method consists of two steps: in the first step, a circular region of interest is found by first isolating the brightest area in the image by means of morphological processing, and in the second step, the Hough transform is used to detect the main circular feature (corresponding to the optical disk) within the positive horizontal gradient image within this region of interest. Initial results on a database of fundus images show that the proposed method is effective and favourable in relation to comparable techniques.