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Image-based plant phenotyping with incremental learning and active contours

Massimo Minervini, Mohammed M. Abdelsamea, Sotirios A. Tsaftaris
2014 Ecological Informatics  
Please cite this article as: Minervini, M., et al., Image-based plant phenotyping with incremental learning and active contours, Ecological Informatics (2013), http://dx.  ...  84.21 (9.08) 91.17 (5.54) Proposed-b 83.25 (10.29) 98.99 (1.10) 82.50 (9.98) 90.08 (6.21) Proposed-c 73.72 (17.82) 99.39 (0.92) 73.21 (17.28) 83.39 (11.92) Please cite this article as: Minervini  ... 
doi:10.1016/j.ecoinf.2013.07.004 fatcat:ibhvjxakbvfrbh567lnbf4r7km

Machine Learning for Plant Phenotyping Needs Image Processing

Sotirios A. Tsaftaris, Massimo Minervini, Hanno Scharr
2016 Trends in Plant Science  
We found the article by Singh et al. [1] extremely interesting since it introduces and showcases the utility of machine learning for high throughput data-driven plant phenotyping.
doi:10.1016/j.tplants.2016.10.002 pmid:27810146 fatcat:o6hwhwnbafculnfckonsrflmuy

The significance of image compression in plant phenotyping applications

Massimo Minervini, Hanno Scharr, Sotirios A. Tsaftaris
2015 Functional Plant Biology  
Until specialized compression 603 algorithms tailored to the problems of plant phenotyping become ubiquitous (Minervini 604 and Tsaftaris 2013; Minervini et al. 2014b), based on our analysis we recommend  ...  Such schemes consist of two parts: an encoder converting compression performance should be evaluated against how accurately the trait of interest 159 can be measured (Minervini and Tsaftaris 2013) .  ... 
doi:10.1071/fp15033 pmid:32480737 fatcat:wxsh6gl2rrdktlmwtnuicquoqm

Finely-grained annotated datasets for image-based plant phenotyping

Massimo Minervini, Andreas Fischbach, Hanno Scharr, Sotirios A. Tsaftaris
2016 Pattern Recognition Letters  
Graphical Abstract Finely-grained annotated datasets for image-based plant phenotyping Massimo Minervini, Andreas Fischbach, Hanno Scharr, Sotirios A.  ...  We devised and released an annotation tool (Minervini et al., 2015a) in order to facilitate future annotation.  ...  In fact, most experts now agree that lack of reliable and automated algorithms to analyze these vast datasets forms a new bottleneck in our understanding of plant biology and function (Minervini et al  ... 
doi:10.1016/j.patrec.2015.10.013 fatcat:sirvorjd6ne7xafqaeeskjwaly

Image Analysis: The New Bottleneck in Plant Phenotyping [Applications Corner]

Massimo Minervini, Hanno Scharr, Sotirios A. Tsaftaris
2015 IEEE Signal Processing Magazine  
[ applications CORNER ] IEEE SIGNAL PROCESSING MAGAZINE [126] juLy 2015 Massimo Minervini, Hanno Scharr, and Sotirios A.  ...  Minervini (m.minervini@ imtlucca.it) is a research associate with IMT Institute of Advanced Studies in Lucca, Italy.  ... 
doi:10.1109/msp.2015.2405111 fatcat:mhdgo7mmv5cmtdpfbzrcggmpzy

Unsupervised and supervised approaches to color space transformation for image coding

Massimo Minervini, Cristian Rusu, Sotirios A. Tsaftaris
2014 2014 IEEE International Conference on Image Processing (ICIP)  
The linear transformation of input (typically RGB) data into a color space is important in image compression. Most schemes adopt fixed transforms to decorrelate the color channels. Energy compaction transforms such as the Karhunen-Loève (KLT) do entail a complexity increase. Here, we propose a new data-dependent transform (aKLT), that achieves compression performance comparable to the KLT, at a fraction of the computational complexity. More important, we also consider an application-aware
more » ... g, in which a classifier analyzes reconstructed images at the receiver's end. In this context, KLT-based approaches may not be optimal and transforms that maximize post-compression classifier performance are more suited. Relaxing energy compactness constraints, we propose for the first time a transform which can be found offline optimizing the Fisher discrimination criterion in a supervised fashion. In lieu of channel decorrelation, we obtain spatial decorrelation using the same color transform as a rudimentary classifier to detect objects of interest in the input image without adding any computational cost. We achieve higher savings encoding these regions at a higher quality, when combined with region-of-interest capable encoders, such as JPEG 2000.
doi:10.1109/icip.2014.7026128 dblp:conf/icip/MinerviniRT14 fatcat:nuboxnvmoffgzhtxl3vpkpa53i

Calmodulin Enhances Cryptochrome Binding to INAD in Drosophila Photoreceptors

Gabriella Margherita Mazzotta, Massimo Bellanda, Giovanni Minervini, Milena Damulewicz, Paola Cusumano, Simona Aufiero, Monica Stefani, Barbara Zambelli, Stefano Mammi, Rodolfo Costa, Silvio C. E. Tosatto
2018 Frontiers in Molecular Neuroscience  
Copyright © 2018 Mazzotta, Bellanda, Minervini, Damulewicz, Cusumano, Aufiero, Stefani, Zambelli, Mammi, Costa and Tosatto.  ... 
doi:10.3389/fnmol.2018.00280 pmid:30177872 pmcid:PMC6109769 fatcat:uh7lwelibbaepo63fprb5zio2y

Computationally Efficient Data and Application Driven Color Transforms for the Compression and Enhancement of Images and Video [chapter]

Massimo Minervini, Cristian Rusu, Sotirios A. Tsaftaris
2015 Color Image and Video Enhancement  
In "Computationally Efficient Data and Application Driven Color Transforms for the Compression and Enhancement of Images and Video," Minervini et al. deal with the problem of efficient coding and transmission  ... 
doi:10.1007/978-3-319-09363-5_13 fatcat:4avcsgxob5f3ncps6n7qqf3ewe

Leaf segmentation in plant phenotyping: a collation study

Hanno Scharr, Massimo Minervini, Andrew P. French, Christian Klukas, David M. Kramer, Xiaoming Liu, Imanol Luengo, Jean-Michel Pape, Gerrit Polder, Danijela Vukadinovic, Xi Yin, Sotirios A. Tsaftaris
2015 Machine Vision and Applications  
Minervini) and was unavailable to all others. Training set numbers are provided by the participants (with the same evaluation function and metrics used also on the testing set).  ... 
doi:10.1007/s00138-015-0737-3 fatcat:c4dmf4exezgi3kiaxdipw3h7ai

Phenotiki: an open software and hardware platform for affordable and easy image-based phenotyping of rosette-shaped plants

Massimo Minervini, Mario V. Giuffrida, Pierdomenico Perata, Sotirios A. Tsaftaris
2017 The Plant Journal  
Minervini et al.  ...  and Tsaftaris, 2013; Minervini et al., 2015c) .  ...  To reduce storage requirements without affecting phenotyping accuracy (Minervini et al., 2015c) , images were encoded at the device using the lossless compression standard available in the PNG file format  ... 
doi:10.1111/tpj.13472 pmid:28066963 fatcat:jihbtp52hnab3hd42o4itftxze

An observational study in psychiatric acute patients admitted to General Hospital Psychiatric Wards in Italy

Andrea Ballerini, Roberto Boccalon, Giancarlo Boncompagni, Massimo Casacchia, Francesco Margari, Lina Minervini, Roberto Righi, Federico Russo, Andrea Salteri
2007 Annals of General Psychiatry  
Objectives: this Italian observational study was aimed at collecting data of psychiatric patients with acute episodes entering General Hospital Psychiatric Wards (GHPWs). Information was focused on diagnosis (DSM-IV), reasons of hospitalisation, prescribed treatment, outcome of aggressive episodes, evolution of the acute episode. Methods: assessments were performed at admission and discharge. Used psychometric scales were the Brief Psychiatric Rating Scale (BPRS), the Modified Overt Aggression
more » ... cale (MOAS) and the Nurses' Observation Scale for Inpatient Evaluation (NOSIE-30). Results: 864 adult patients were enrolled in 15 GHPWs: 728 (320 M; mean age 43.6 yrs) completed both admission and discharge visits. A severe psychotic episode with (19.1%) or without (47.7%) aggressive behaviour was the main reason of admission. Schizophrenia (42.8% at admission and 40.1% at discharge) and depression (12.9% at admission and 14.7% at discharge) were the predominant diagnoses. The mean hospital stay was 12 days. The mean (± SD) total score of MOAS at admission, day 7 and discharge was, respectively, 2.53 ± 5.1, 0.38 ± 2.2, and 0.21 ± 1.5. Forty-four (6.0%) patients had episodes of aggressiveness at admission and 8 (1.7%) at day 7. A progressive improvement in each domain/ item vs. admission was observed for MOAS and BPRS, while NOSIE-30 did not change from day 4 onwards. The number of patients with al least one psychotic drug taken at admission, in the first 7 days of hospitalisation, and prescribed at discharge, was, respectively: 472 (64.8%), 686 (94.2%) and 676 (92.9%). The respective most frequently psychotic drugs were: BDZs (60.6%, 85.7%, 69.5%), typical anti-psychotics (48.3%, 57.0%, 49.6%), atypical anti-psychotics (35.6%, 41.8%, 39.8%) and antidepressants (40.9%, 48.8%, 43.2%). Rates of patients with one, two or > 2 psychotic drugs taken at admission and day 7, and prescribed at discharge, were, respectively: 24.8%, 8.2% and 13.5% in mono-therapy; 22.0%, 20.6% and 26.6% with two drugs, and 53.2%, 57.8% and 59.0% with > two drugs. Benzodiazepines were the most common drugs both at admission (60.0%) and during hospitalisation (85.7%), and 69.5% were prescribed at discharge. Conclusion: patients with psychiatric diseases in acute phase experienced a satisfactory outcome following intensified therapeutic interventions during hospitalisation.
doi:10.1186/1744-859x-6-2 pmid:17257438 pmcid:PMC1805444 fatcat:iydvdmu74rar5c5iyx3nfsngte

Large-scale analysis of neuroimaging data on commercial clouds with content-aware resource allocation strategies

Massimo Minervini, Cristian Rusu, Mario Damiano, Valter Tucci, Angelo Bifone, Alessandro Gozzi, Sotirios A Tsaftaris
2014 The international journal of high performance computing applications  
The combined use of mice that have genetic mutations (transgenic mouse models) of human pathology and advanced neuroimaging methods (such as MRI) has the potential to radically change how we approach disease understanding, diagnosis and treatment. Morphological changes occurring in the brain of transgenic animals as a result of the interaction between environment and genotype, can be assessed using advanced image analysis methods, an effort described as "mouse brain phenotyping". However, the
more » ... mputational methods involved in the analysis of high-resolution brain images are demanding. While running such analysis on local clusters is possible, not all users have access to such infrastructure and even for those that do, having additional computational capacity can be beneficial (e.g., to meet sudden high throughput demands). In this paper we use a commercial cloud platform for brain neuroimaging and analysis. We achieve a registration-based multi-atlas, multi-template anatomical segmentation, normally a lengthy in time effort, within a few hours. Naturally, performing such analyses on the cloud entails a monetary cost, and it is worthwhile identifying strategies that can allocate resources intelligently. In our context a critical aspect is the identification of how long each job will take. We propose a method that estimates the complexity of an image processing task, a registration, using statistical moments and shape descriptors of the image content. We use this information to learn and predict the completion time of a registration. The proposed approach is easy to deploy, and could serve as an alternative for laboratories that may require instant access to large high performance computing infrastructures. To facilitate adoption from the community we release publicly the source code.
doi:10.1177/1094342013519483 fatcat:qtchpzss2fhjtikjjfebg5kjmu

Main clinical features in patients at their first psychiatric admission to Italian acute hospital psychiatric wards. The PERSEO study

Andrea Ballerini, Roberto M Boccalon, Giancarlo Boncompagni, Massimo Casacchia, Francesco Margari, Lina Minervini, Roberto Righi, Federico Russo, Andrea Salteri, Sonia Frediani, Andrea Rossi, Marco Scatigna
2007 BMC Psychiatry  
Few data are available on subjects presenting to acute wards for the first time with psychotic symptoms. The aims of this paper are (i) to describe the epidemiological and clinical characteristics of patients at their first psychiatric admission (FPA), including socio-demographic features, risk factors, life habits, modalities of onset, psychiatric diagnoses and treatments before admission; (ii) to assess the aggressive behavior and the clinical management of FPA patients in Italian acute
more » ... al psychiatric wards, called SPDCs (Servizio Psichiatrico Diagnosi e Cura = psychiatric service for diagnosis and management). Method: Cross-sectional observational multi-center study involving 62 Italian SPDCs (PERSEO -Psychiatric EmeRgency Study and EpidemiOlogy). Results: 253 FPA aged <= 40 were identified among 2521 patients admitted to Italian SPDCs over the 5-month study period. About half of FPA patients showed an aggressive behavior as defined by a Modified Overt Aggression Scale (MOAS) score greater than 0 Vs 46% of non-FPA patients (p = 0.3651). The most common was verbal aggression, while about 20% of FPA patients actually engaged in physical aggression against other people. 74% of FPA patients had no diagnosis at admission, while 40% had received a previous psychopharmacological treatment, mainly benzodiazepines and antidepressants. During SPDC stay, diagnosis was established in 96% of FPA patients and a pharmacological therapy was prescribed to 95% of them, mainly benzodiazepines, antipsychotics and mood stabilizers. Conclusion: Subjects presenting at their first psychiatric ward admission have often not undergone previous adequate psychiatric assessment and diagnostic procedures. The first hospital admission allows diagnosis and psychopharmacological treatment to be established. In our population, aggressive behaviors were rather frequent, although most commonly verbal. Psychiatric symptoms, as evaluated by psychiatrists and patients, improved significantly from admission to discharge both for FPA and non-FPA patients.
doi:10.1186/1471-244x-7-3 pmid:17239235 pmcid:PMC1785379 fatcat:dnonzbknprbmflgo5mh3l6vtoi

Multicentre International Study for the Prevention with iAluRil of Radio-induced Cystitis (MISTIC): A Randomised Controlled Study

Juan Palou Redorta, Francesco Sanguedolce, Gemma Sancho Pardo, Martin Romancik, Gianni Vittori, Andrea Minervini, Fabrizio Di Maida, Richard Lunik, Renzo Colombo, Vincenzo Serretta, Bülent Çetinel, Vittorio Bini (+2 others)
2021 European Urology Open Science  
Critical revision of the manuscript for important intellectual content: Palou Redorta, Minervini. Statistical analysis: Bini. Obtaining funding: None.  ...  Author contributions: Massimo Lazzeri had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.  ... 
doi:10.1016/j.euros.2021.01.016 pmid:34337507 pmcid:PMC8317871 fatcat:av3xk644hzhhpopfbgtwo32iwa

Clinical features and therapeutic management of patients admitted to Italian acute hospital psychiatric units: the PERSEO (Psychiatric EmeRgency Study and EpidemiOlogy) survey

Andrea Ballerini, Roberto M Boccalon, Giancarlo Boncompagni, Massimo Casacchia, Francesco Margari, Lina Minervini, Roberto Righi, Federico Russo, Andrea Salteri, Sonia Frediani, Andrea Rossi, Marco Scatigna (+1 others)
2007 Annals of General Psychiatry  
The PERSEO study (psychiatric emergency study and epidemiology) is a naturalistic, observational clinical survey in Italian acute hospital psychiatric units, called SPDCs (Servizio Psichiatrico Diagnosi e Cura; in English, the psychiatric service for diagnosis and management). The aims of this paper are: (i) to describe the epidemiological and clinical characteristics of patients, including sociodemographic features, risk factors, life habits and psychiatric diagnoses; and (ii) to assess the
more » ... nical management, subjective wellbeing and attitudes toward medications. Methods: A total of 62 SPDCs distributed throughout Italy participated in the study and 2521 patients were enrolled over the 5-month study period. Results: Almost half of patients (46%) showed an aggressive behaviour at admission to ward, but they engaged more commonly in verbal aggression (38%), than in aggression toward other people (20%). A total of 78% of patients had a psychiatric diagnosis at admission, most frequently schizophrenia (36%), followed by depression (16%) and personality disorders (14%), and no relevant changes in the diagnoses pattern were observed during hospital stay. Benzodiazepines were the most commonly prescribed drugs, regardless of diagnosis, at all time points. Overall, up to 83% of patients were treated with neuroleptic drugs and up to 27% received more than one neuroleptic either during hospital stay or at discharge. Atypical and conventional antipsychotics were equally prescribed for schizophrenia (59 vs 65% during stay and 59 vs 60% at discharge), while
doi:10.1186/1744-859x-6-29 pmid:17983468 pmcid:PMC2186309 fatcat:sjbfcbotlfgyjduz4d23rn4dku
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