Adaptive Bacteria Colony Picking in Unstructured Environments Using Intensity Histogram and Unascertained LS-SVM Classifier

Features analysis is an important task which can significantly affect the performance of automatic bacteria colony picking. Unstructured environments also affect the automatic colony screening. This paper presents a novel approach for adaptive colony segmentation in unstructured environments by treating the detected peaks of intensity histograms as a morphological feature of images. In order to avoid disturbing peaks, an entropy based mean shift filter is introduced to smooth images as a preprocessing step. The relevance and importance of these features can be determined in an improved support vector machine classifier using unascertained least square estimation. Experimental results show that the proposed unascertained least square support vector machine (ULSSVM) has better recognition accuracy than the other state-of-the-art techniques, and its training process takes less time than most of the traditional approaches presented in this paper.

Histogram of oriented gradients front end processing: An FPGA based processor approach

The Field Programmable Gate Array (FPGA) implementation of the commonly used Histogram of Oriented Gradients (HOG) algorithm is explored. The HOG algorithm is employed to extract features for object detection. A key focus has been to explore the use of a new FPGA-based processor which has been targeted at image processing. The paper gives details of the mapping and scheduling factors that influence the performance and the stages that were undertaken to allow the algorithm to be deployed on FPGA hardware, whilst taking into account the specific IPPro architecture features. We show that multi-core IPPro performance can exceed that of against state-of-the-art FPGA designs by up to 3.2 times with reduced design and implementation effort and increased flexibility all on a low cost, Zynq programmable system.

Whole Slide Image Cytometry: a Novel Method for the Detection and Quantification of Abnormal DNA Contents in Barrett’s Oesophagus

Background: Barrett's oesophagus (BO) is a well recognized precursor of the majority of cases of oesophageal adenocarcinoma (OAC). Endoscopic surveillance of BO patients is frequently undertaken in an attempt to detect early OAC, high grade dysplasia (HGD) or low grade dysplasia (LGD). However histological interpretation and grading of dysplasia is subjective and poorly reproducible. The alternative flow cytometry and cytology-preparation image cytometry techniques require large amounts of tissue and specialist expertise which are not widely available for frontline health care.
Methods: This study has combined whole slide imaging with DNA image cytometry, to provide a novel method for the detection and quantification of abnormal DNA contents. 20 cases were evaluated, including 8 Barrett's specialised intestinal metaplasia (SIM), 6 LGD and 6 HGD. Feulgen stained oesophageal sections (1µm thickness) were digitally scanned in their entirety and evaluated to select regions of interests and abnormalities. Barrett’s mucosa was then interactively chosen for automatic nuclei segmentation where irrelevant cell types are ignored. The combined DNA content histogram for all selected image regions was then obtained. In addition, histogram measurements, including 5c exceeding ratio (xER-5C), 2c deviation index (2cDI) and DNA grade of malignancy (DNA-MG), were computed.
Results: The histogram measurements, xER-5C, 2cDI and DNA-MG, were shown to be effective in differentiating SIM from HGD, SIM from LGD, and LGD from HGD. All three measurements discriminated SIM from HGD cases successfully with statistical significance (pxER-5C=0.0041, p2cDI=0.0151 and pDNA-MG=0.0057). Statistical significance is also achieved differentiating SIM from LGD samples with pxER-5C=0.0019, p2cDI=0.0023 and pDNA-MG=0.0030. Furthermore the differences between LGD and HGD cases are statistical significant (pxER-5C=0.0289, p2cDI=0.0486 and pDNA-MG=0.0384).
Conclusion: Whole slide image cytometry is a novel and effective method for the detection and quantification of abnormal DNA content in BO. Compared to manual histological review, this proposed method is more objective and reproducible. Compared to flow cytometry and cytology-preparation image cytometry, the current method is low cost, simple to use and only requires a single 1µm tissue section. Whole slide image cytometry could assist the routine clinical diagnosis of dysplasia in BO, which is relevant for future progression risk to OAC.

A sparse representation based fast detection method for surface defect detection of bottle caps

A practical machine-vision-based system is developed for fast detection of defects occurring on the surface of bottle caps. This system can be used to extract the circular region as the region of interests (ROI) from the surface of a bottle cap, and then use the circular region projection histogram (CRPH) as the matching features. We establish two dictionaries for the template and possible defect, respectively. Due to the requirements of high-speed production as well as detecting quality, a fast algorithm based on a sparse representation is proposed to speed up the searching. In the sparse representation, non-zero elements in the sparse factors indicate the defect's size and position. Experimental results in industrial trials show that the proposed method outperforms the orientation code method (OCM) and is able to produce promising results for detecting defects on the surface of bottle caps.

Management of Bartholin's gland carcinoma using high-dose-rate interstitial brachytherapy boost

To describe the patterns of use, clinical outcomes, and dose-volume histogram parameters of high-dose-rate interstitial brachytherapy (HDR-ISBT) in the management of Bartholin's gland cancer.

Predictors of Chest Wall Toxicity after Lung Stereotactic Ablative Radiotherapy

AIMS: To determine the incidence and predictive factors of rib fracture and chest wall pain after lung stereotactic ablative radiotherapy (SABR).

MATERIALS AND METHODS: Patients were treated with lung SABR of 48-60 Gy in four to five fractions. The treatment plan and follow-up computed tomography scans of 289 tumours in 239 patients were reviewed. Dose-volume histogram (DVH) metrics and clinical factors were evaluated as potential predictors of chest wall toxicity.

RESULTS: The median follow-up was 21.0 months (range 6.2-52.1). Seventeen per cent (50/289) developed a rib fracture, 44% (22/50) were symptomatic; the median time to fracture was 16.4 months. On univariate analysis, female gender, osteoporosis, tumours adjacent (within 5 mm) to the chest wall and all of the chest wall DVH metrics predicted for rib fracture, but only tumour location adjacent to the chest wall remained significant on the multivariate model (P < 0.01). The 2 year fracture-free probability for those adjacent to the chest wall was 65.6%. Among those tumours adjacent to the chest wall, only osteoporosis (P = 0.02) predicted for fracture, whereas none of the chest wall DVH metrics were predictive. Eight per cent (24/289) experienced chest wall pain without fracture.

CONCLUSIONS: None of the chest wall DVH metrics independently predicted for SABR-induced rib fracture when tumour location is taken into account. Patients with tumours adjacent (within 5 mm) to the chest wall are at greater risk of rib fracture after lung SABR, and among these, an additional risk was observed in osteoporotic patients.

The Impact of Colleague Peer Review on the Radiotherapy Treatment Planning Process in the Radical Treatment of Lung Cancer

AIMS: Modern radiotherapy uses techniques to reliably identify tumour and reduce target volume margins. However, this can potentially lead to an increased risk of geographic miss. One source of error is the accuracy of target volume delineation (TVD). Colleague peer review (CPR) of all curative-intent lung cancer plans has been mandatory in our institution since May 2013. At least two clinical oncologists review plans, checking treatment paradigm, TVD, prescription dose tumour and critical organ tolerances. We report the impact of CPR in our institution.

MATERIALS AND METHODS: Radiotherapy treatment plans of all patients receiving radical radiotherapy were presented at weekly CPR meetings after their target volumes were reviewed and signed off by the treating consultant. All cases and any resultant change to TVD (including organs at risk) or treatment intent were recorded in our prospective CPR database. The impact of CPR over a 13 month period from May 2013 to June 2014 is reported.

RESULTS: One hundred and twenty-two patients (63% non-small cell lung carcinoma, 17% small cell lung carcinoma and 20% 'clinical diagnosis') were analysed. On average, 3.2 cases were discussed per meeting (range 1-8). CPR resulted in a change in treatment paradigm in 3% (one patient proceeded to induction chemotherapy, two patients had high-dose palliative radiotherapy). Twenty-one (17%) had a change in TVD and one (1%) patient had a change in dose prescription. In total, 6% of patients had plan adjustment after review of dose volume histogram.

CONCLUSION: The introduction of CPR in our centre has resulted in a change in a component of the treatment plan for 27% of patients receiving curative-intent lung radiotherapy. We recommend CPR as a mandatory quality assurance step in the planning process of all radical lung plans.

FPGA Soft-core Processors, Compiler and Hardware Optimizations validated using HOG

There is demand for an easily programmable, high performance image processing platform based on FPGAs. In previous work, a novel, high performance processor - IPPro was developed and a Histogram of Orientated Gradients (HOG) algorithm study undertaken on a Xilinx Zynq platform. Here, we identify and explore a number of mapping strategies to improve processing efficiency for soft-cores and a number of options for creation of a division coprocessor. This is demonstrated for the revised high definition HOG implementation on a Zynq platform, resulting in a performance of 328 fps which represents a 146% speed improvement over the original realization and a tenfold reduction in energy.

Video anomaly detection in real-time on a Power-Aware Heterogeneous Platform

FPGAs and GPUs are often used when real-time performance in video processing is required. An accelerated processor is chosen based on task-specific priorities (power consumption, processing time and detection accuracy), and this decision is normally made once at design time. All three characteristics are important, particularly in battery-powered systems. Here we propose a method for moving selection of processing platform from a single design-time choice to a continuous run time one.We implement Histogram of Oriented Gradients (HOG) detectors for cars and people and Mixture of Gaussians (MoG) motion detectors running across FPGA, GPU and CPU in a heterogeneous system. We use this to detect illegally parked vehicles in urban scenes. Power, time and accuracy information for each detector is characterised. An anomaly measure is assigned to each detected object based on its trajectory and location, when compared to learned contextual movement patterns. This drives processor and implementation selection, so that scenes with high behavioural anomalies are processed with faster but more power hungry implementations, but routine or static time periods are processed with power-optimised, less accurate, slower versions. Real-time performance is evaluated on video datasets including i-LIDS. Compared to power-optimised static selection, automatic dynamic implementation mapping is 10% more accurate but draws 12W extra power in our testbed desktop system.

FPGA-based soft-core processors for image processing applications

With security and surveillance, there is an increasing need to process image data efficiently and effectively either at source or in a large data network. Whilst a Field-Programmable Gate Array (FPGA) has been seen as a key technology for enabling this, the design process has been viewed as problematic in terms of the time and effort needed for implementation and verification. The work here proposes a different approach of using optimized FPGA-based soft-core processors which allows the user to exploit the task and data level parallelism to achieve the quality of dedicated FPGA implementations whilst reducing design time. The paper also reports some preliminary
progress on the design flow to program the structure. An implementation for a Histogram of Gradients algorithm is also reported which shows that a performance of 328 fps can be achieved with this design approach, whilst avoiding the long design time, verification and debugging steps associated with conventional FPGA implementations.